Commit
·
1339be4
1
Parent(s):
475c47e
initial
Browse files- README.md +312 -0
- added_tokens.json +1 -0
- config.json +35 -0
- optimizer.pt +3 -0
- pytorch_model.bin +3 -0
- rng_state.pth +3 -0
- runs/Apr17_09-15-38_delilah/1650208078.0177557/events.out.tfevents.1650208078.delilah.1673820.1 +3 -0
- runs/Apr17_09-15-38_delilah/events.out.tfevents.1650208078.delilah.1673820.0 +3 -0
- runs/Apr20_13-31-29_delilah/1650479523.0943172/events.out.tfevents.1650479523.delilah.16090.1 +3 -0
- runs/Apr20_13-31-29_delilah/events.out.tfevents.1650479523.delilah.16090.0 +3 -0
- runs/Apr20_13-31-46_delilah/1650479523.0845559/events.out.tfevents.1650479523.delilah.16500.1 +3 -0
- runs/Apr20_13-31-46_delilah/events.out.tfevents.1650479523.delilah.16500.0 +3 -0
- runs/Apr20_13-58-10_delilah/1650481104.9475336/events.out.tfevents.1650481104.delilah.41141.1 +3 -0
- runs/Apr20_13-58-10_delilah/events.out.tfevents.1650481104.delilah.41141.0 +3 -0
- runs/May16_17-58-59_delilah/1652743313.9479656/events.out.tfevents.1652743313.delilah.3361827.1 +3 -0
- runs/May16_17-58-59_delilah/events.out.tfevents.1652743313.delilah.3361827.0 +3 -0
- runs/May16_17-58-59_delilah/events.out.tfevents.1654218281.delilah.3361827.2 +3 -0
- scheduler.pt +3 -0
- special_tokens_map.json +1 -0
- spm.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- trainer_state.json +0 -0
- training_args.bin +3 -0
README.md
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| 1 |
+
---
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+
tags:
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+
- generated_from_trainer
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+
model-index:
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+
- name: deberta-v3-large-ddlm
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+
results: []
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+
---
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| 8 |
+
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| 9 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+
should probably proofread and complete it, then remove this comment. -->
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| 11 |
+
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| 12 |
+
# deberta-v3-large-ddlm
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+
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| 14 |
+
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/models/microsoft/deberta-v3-large) on an unknown dataset.
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| 15 |
+
It achieves the following results on the evaluation set:
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+
- Loss: 0.5241
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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+
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+
## Training and evaluation data
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More information needed
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## Training procedure
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| 31 |
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| 32 |
+
### Training hyperparameters
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| 33 |
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 2
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+
- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| 48 |
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|:-------------:|:-----:|:------:|:---------------:|
|
| 49 |
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| 0.9823 | 0.01 | 1000 | 0.9163 |
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| 50 |
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| 0.8817 | 0.02 | 2000 | 0.9022 |
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| 51 |
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| 0.9647 | 0.03 | 3000 | 0.8879 |
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| 52 |
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| 0.8646 | 0.04 | 4000 | 0.8577 |
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| 53 |
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| 0.9159 | 0.06 | 5000 | 0.8677 |
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| 54 |
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| 0.8449 | 0.07 | 6000 | 0.8221 |
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| 55 |
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| 0.8681 | 0.08 | 7000 | 0.8332 |
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| 56 |
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| 0.8738 | 0.09 | 8000 | 0.8334 |
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| 57 |
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| 0.8638 | 0.1 | 9000 | 0.8236 |
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| 58 |
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| 0.9066 | 0.11 | 10000 | 0.8200 |
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| 59 |
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| 0.8686 | 0.12 | 11000 | 0.8092 |
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| 60 |
+
| 0.7736 | 0.13 | 12000 | 0.8199 |
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| 61 |
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| 0.8054 | 0.14 | 13000 | 0.7972 |
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| 62 |
+
| 0.8934 | 0.16 | 14000 | 0.7998 |
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| 63 |
+
| 0.7884 | 0.17 | 15000 | 0.7895 |
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| 64 |
+
| 0.8278 | 0.18 | 16000 | 0.7586 |
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| 65 |
+
| 0.8482 | 0.19 | 17000 | 0.7562 |
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| 66 |
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| 0.8716 | 0.2 | 18000 | 0.7819 |
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| 67 |
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| 0.8881 | 0.21 | 19000 | 0.7878 |
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| 68 |
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| 0.8397 | 0.22 | 20000 | 0.7989 |
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| 69 |
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| 0.811 | 0.23 | 21000 | 0.7846 |
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| 70 |
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| 0.7762 | 0.24 | 22000 | 0.7753 |
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| 71 |
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| 0.7778 | 0.25 | 23000 | 0.7878 |
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| 72 |
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| 0.737 | 0.27 | 24000 | 0.7473 |
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| 73 |
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| 0.8451 | 0.28 | 25000 | 0.7460 |
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| 74 |
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| 0.823 | 0.29 | 26000 | 0.7300 |
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| 75 |
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| 0.7472 | 0.3 | 27000 | 0.7292 |
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| 76 |
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| 0.8048 | 0.31 | 28000 | 0.7697 |
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| 77 |
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| 0.7962 | 0.32 | 29000 | 0.7359 |
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| 78 |
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| 0.8048 | 0.33 | 30000 | 0.7409 |
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| 79 |
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| 0.8095 | 0.34 | 31000 | 0.7434 |
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| 80 |
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| 0.7451 | 0.35 | 32000 | 0.7534 |
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| 81 |
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| 0.6997 | 0.37 | 33000 | 0.7602 |
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| 82 |
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| 0.8116 | 0.38 | 34000 | 0.7566 |
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| 83 |
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| 0.7963 | 0.39 | 35000 | 0.7245 |
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| 84 |
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| 0.786 | 0.4 | 36000 | 0.7311 |
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| 85 |
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| 0.7991 | 0.41 | 37000 | 0.7230 |
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| 86 |
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| 0.723 | 0.42 | 38000 | 0.7209 |
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| 87 |
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| 0.789 | 0.43 | 39000 | 0.7418 |
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| 88 |
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| 0.7296 | 0.44 | 40000 | 0.7325 |
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| 89 |
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| 0.7363 | 0.45 | 41000 | 0.7134 |
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| 90 |
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| 0.758 | 0.47 | 42000 | 0.6948 |
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| 91 |
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| 0.711 | 0.48 | 43000 | 0.6992 |
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| 92 |
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| 0.7984 | 0.49 | 44000 | 0.7055 |
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| 93 |
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| 0.8402 | 0.5 | 45000 | 0.7108 |
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| 94 |
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| 0.8553 | 0.51 | 46000 | 0.7005 |
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| 95 |
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| 0.7538 | 0.52 | 47000 | 0.7208 |
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| 96 |
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| 0.7169 | 0.53 | 48000 | 0.7291 |
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| 97 |
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| 0.7345 | 0.54 | 49000 | 0.7195 |
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| 98 |
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| 0.758 | 0.55 | 50000 | 0.6694 |
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| 99 |
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| 0.7868 | 0.56 | 51000 | 0.6938 |
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| 100 |
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| 0.6966 | 0.58 | 52000 | 0.6867 |
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| 101 |
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| 0.7389 | 0.59 | 53000 | 0.6862 |
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| 102 |
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| 0.7529 | 0.6 | 54000 | 0.7175 |
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| 103 |
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| 0.7345 | 0.61 | 55000 | 0.6970 |
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| 104 |
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| 0.766 | 0.62 | 56000 | 0.7017 |
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| 105 |
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| 0.7043 | 0.63 | 57000 | 0.6916 |
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| 106 |
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| 0.6474 | 0.64 | 58000 | 0.7129 |
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| 107 |
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| 0.7456 | 0.65 | 59000 | 0.6802 |
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| 108 |
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| 0.7512 | 0.66 | 60000 | 0.6951 |
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| 109 |
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| 0.6816 | 0.68 | 61000 | 0.7072 |
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| 110 |
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| 0.7206 | 0.69 | 62000 | 0.6967 |
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| 111 |
+
| 0.6439 | 0.7 | 63000 | 0.6798 |
|
| 112 |
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| 0.7309 | 0.71 | 64000 | 0.7163 |
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| 113 |
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| 0.6925 | 0.72 | 65000 | 0.6794 |
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| 114 |
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| 0.6833 | 0.73 | 66000 | 0.6637 |
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| 115 |
+
| 0.6643 | 0.74 | 67000 | 0.6855 |
|
| 116 |
+
| 0.6433 | 0.75 | 68000 | 0.7035 |
|
| 117 |
+
| 0.7595 | 0.76 | 69000 | 0.7008 |
|
| 118 |
+
| 0.7214 | 0.78 | 70000 | 0.6618 |
|
| 119 |
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| 0.7111 | 0.79 | 71000 | 0.6850 |
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| 120 |
+
| 0.7375 | 0.8 | 72000 | 0.6909 |
|
| 121 |
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| 0.6779 | 0.81 | 73000 | 0.7042 |
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| 122 |
+
| 0.6646 | 0.82 | 74000 | 0.6634 |
|
| 123 |
+
| 0.6616 | 0.83 | 75000 | 0.7020 |
|
| 124 |
+
| 0.6762 | 0.84 | 76000 | 0.6638 |
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| 125 |
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| 0.7509 | 0.85 | 77000 | 0.6541 |
|
| 126 |
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| 0.6963 | 0.86 | 78000 | 0.6781 |
|
| 127 |
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| 0.6949 | 0.87 | 79000 | 0.6576 |
|
| 128 |
+
| 0.6781 | 0.89 | 80000 | 0.6900 |
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| 129 |
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| 0.65 | 0.9 | 81000 | 0.6835 |
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| 130 |
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| 0.7205 | 0.91 | 82000 | 0.6712 |
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| 131 |
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| 0.6901 | 0.92 | 83000 | 0.6699 |
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| 132 |
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| 0.6972 | 0.93 | 84000 | 0.6456 |
|
| 133 |
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| 0.7041 | 0.94 | 85000 | 0.6497 |
|
| 134 |
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| 0.6864 | 0.95 | 86000 | 0.6432 |
|
| 135 |
+
| 0.7308 | 0.96 | 87000 | 0.6497 |
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| 136 |
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| 0.6886 | 0.97 | 88000 | 0.6674 |
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| 137 |
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| 0.6947 | 0.99 | 89000 | 0.6638 |
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| 138 |
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| 0.6567 | 1.0 | 90000 | 0.6242 |
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| 139 |
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| 0.7185 | 1.01 | 91000 | 0.6704 |
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| 140 |
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| 0.7435 | 1.02 | 92000 | 0.6681 |
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| 141 |
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| 0.7108 | 1.03 | 93000 | 0.6619 |
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| 142 |
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| 0.6942 | 1.04 | 94000 | 0.6306 |
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| 143 |
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| 0.6998 | 1.05 | 95000 | 0.6409 |
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| 144 |
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| 0.6481 | 1.06 | 96000 | 0.6476 |
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| 145 |
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| 0.727 | 1.07 | 97000 | 0.6354 |
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| 146 |
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| 0.647 | 1.09 | 98000 | 0.6222 |
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| 147 |
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| 0.6622 | 1.1 | 99000 | 0.6119 |
|
| 148 |
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| 0.6346 | 1.11 | 100000 | 0.6471 |
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| 149 |
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| 0.6203 | 1.12 | 101000 | 0.6655 |
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| 150 |
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| 0.6765 | 1.13 | 102000 | 0.6473 |
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| 151 |
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| 0.6703 | 1.14 | 103000 | 0.6308 |
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| 152 |
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| 0.6793 | 1.15 | 104000 | 0.6531 |
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| 153 |
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| 0.683 | 1.16 | 105000 | 0.6693 |
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| 154 |
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| 0.6654 | 1.17 | 106000 | 0.6241 |
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| 155 |
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| 0.6626 | 1.18 | 107000 | 0.6215 |
|
| 156 |
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| 0.6976 | 1.2 | 108000 | 0.6479 |
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| 157 |
+
| 0.7494 | 1.21 | 109000 | 0.6345 |
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| 158 |
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| 0.691 | 1.22 | 110000 | 0.6322 |
|
| 159 |
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| 0.6568 | 1.23 | 111000 | 0.6265 |
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| 160 |
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| 0.705 | 1.24 | 112000 | 0.6281 |
|
| 161 |
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| 0.6307 | 1.25 | 113000 | 0.6202 |
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| 162 |
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| 0.6828 | 1.26 | 114000 | 0.6158 |
|
| 163 |
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| 0.6403 | 1.27 | 115000 | 0.6495 |
|
| 164 |
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| 0.6615 | 1.28 | 116000 | 0.6298 |
|
| 165 |
+
| 0.6237 | 1.3 | 117000 | 0.6234 |
|
| 166 |
+
| 0.6707 | 1.31 | 118000 | 0.6267 |
|
| 167 |
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| 0.6823 | 1.32 | 119000 | 0.6299 |
|
| 168 |
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| 0.6333 | 1.33 | 120000 | 0.6169 |
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| 169 |
+
| 0.685 | 1.34 | 121000 | 0.6371 |
|
| 170 |
+
| 0.6941 | 1.35 | 122000 | 0.6245 |
|
| 171 |
+
| 0.6358 | 1.36 | 123000 | 0.6291 |
|
| 172 |
+
| 0.6754 | 1.37 | 124000 | 0.6400 |
|
| 173 |
+
| 0.6286 | 1.38 | 125000 | 0.6148 |
|
| 174 |
+
| 0.7036 | 1.4 | 126000 | 0.6033 |
|
| 175 |
+
| 0.645 | 1.41 | 127000 | 0.6295 |
|
| 176 |
+
| 0.6578 | 1.42 | 128000 | 0.6348 |
|
| 177 |
+
| 0.651 | 1.43 | 129000 | 0.6222 |
|
| 178 |
+
| 0.5558 | 1.44 | 130000 | 0.6231 |
|
| 179 |
+
| 0.6601 | 1.45 | 131000 | 0.6302 |
|
| 180 |
+
| 0.6304 | 1.46 | 132000 | 0.6127 |
|
| 181 |
+
| 0.6177 | 1.47 | 133000 | 0.6047 |
|
| 182 |
+
| 0.5933 | 1.48 | 134000 | 0.6169 |
|
| 183 |
+
| 0.6307 | 1.49 | 135000 | 0.6012 |
|
| 184 |
+
| 0.6018 | 1.51 | 136000 | 0.5900 |
|
| 185 |
+
| 0.6724 | 1.52 | 137000 | 0.6086 |
|
| 186 |
+
| 0.6367 | 1.53 | 138000 | 0.6414 |
|
| 187 |
+
| 0.6515 | 1.54 | 139000 | 0.6267 |
|
| 188 |
+
| 0.5902 | 1.55 | 140000 | 0.5913 |
|
| 189 |
+
| 0.6523 | 1.56 | 141000 | 0.5992 |
|
| 190 |
+
| 0.6005 | 1.57 | 142000 | 0.6128 |
|
| 191 |
+
| 0.6179 | 1.58 | 143000 | 0.6089 |
|
| 192 |
+
| 0.6154 | 1.59 | 144000 | 0.6353 |
|
| 193 |
+
| 0.6298 | 1.61 | 145000 | 0.5997 |
|
| 194 |
+
| 0.5623 | 1.62 | 146000 | 0.5974 |
|
| 195 |
+
| 0.5787 | 1.63 | 147000 | 0.6165 |
|
| 196 |
+
| 0.6099 | 1.64 | 148000 | 0.6246 |
|
| 197 |
+
| 0.658 | 1.65 | 149000 | 0.6116 |
|
| 198 |
+
| 0.6567 | 1.66 | 150000 | 0.5938 |
|
| 199 |
+
| 0.6227 | 1.67 | 151000 | 0.5948 |
|
| 200 |
+
| 0.5858 | 1.68 | 152000 | 0.5822 |
|
| 201 |
+
| 0.6227 | 1.69 | 153000 | 0.5802 |
|
| 202 |
+
| 0.6699 | 1.71 | 154000 | 0.6067 |
|
| 203 |
+
| 0.5989 | 1.72 | 155000 | 0.6073 |
|
| 204 |
+
| 0.6184 | 1.73 | 156000 | 0.6124 |
|
| 205 |
+
| 0.6404 | 1.74 | 157000 | 0.6169 |
|
| 206 |
+
| 0.639 | 1.75 | 158000 | 0.5997 |
|
| 207 |
+
| 0.6433 | 1.76 | 159000 | 0.5989 |
|
| 208 |
+
| 0.5574 | 1.77 | 160000 | 0.5796 |
|
| 209 |
+
| 0.5983 | 1.78 | 161000 | 0.6036 |
|
| 210 |
+
| 0.6532 | 1.79 | 162000 | 0.5888 |
|
| 211 |
+
| 0.6679 | 1.8 | 163000 | 0.6038 |
|
| 212 |
+
| 0.62 | 1.82 | 164000 | 0.5984 |
|
| 213 |
+
| 0.5541 | 1.83 | 165000 | 0.6003 |
|
| 214 |
+
| 0.6192 | 1.84 | 166000 | 0.5786 |
|
| 215 |
+
| 0.6613 | 1.85 | 167000 | 0.6064 |
|
| 216 |
+
| 0.5923 | 1.86 | 168000 | 0.6018 |
|
| 217 |
+
| 0.5894 | 1.87 | 169000 | 0.5912 |
|
| 218 |
+
| 0.6462 | 1.88 | 170000 | 0.5902 |
|
| 219 |
+
| 0.5811 | 1.89 | 171000 | 0.6030 |
|
| 220 |
+
| 0.6358 | 1.9 | 172000 | 0.5915 |
|
| 221 |
+
| 0.614 | 1.92 | 173000 | 0.5886 |
|
| 222 |
+
| 0.5969 | 1.93 | 174000 | 0.6084 |
|
| 223 |
+
| 0.6146 | 1.94 | 175000 | 0.6003 |
|
| 224 |
+
| 0.6051 | 1.95 | 176000 | 0.5835 |
|
| 225 |
+
| 0.6268 | 1.96 | 177000 | 0.5999 |
|
| 226 |
+
| 0.6436 | 1.97 | 178000 | 0.5965 |
|
| 227 |
+
| 0.6167 | 1.98 | 179000 | 0.5789 |
|
| 228 |
+
| 0.5647 | 1.99 | 180000 | 0.5669 |
|
| 229 |
+
| 0.6038 | 2.0 | 181000 | 0.6009 |
|
| 230 |
+
| 0.6082 | 2.02 | 182000 | 0.5799 |
|
| 231 |
+
| 0.6483 | 2.03 | 183000 | 0.5716 |
|
| 232 |
+
| 0.5503 | 2.04 | 184000 | 0.5806 |
|
| 233 |
+
| 0.6231 | 2.05 | 185000 | 0.5699 |
|
| 234 |
+
| 0.5892 | 2.06 | 186000 | 0.5979 |
|
| 235 |
+
| 0.5933 | 2.07 | 187000 | 0.5709 |
|
| 236 |
+
| 0.594 | 2.08 | 188000 | 0.5719 |
|
| 237 |
+
| 0.5838 | 2.09 | 189000 | 0.5879 |
|
| 238 |
+
| 0.6039 | 2.1 | 190000 | 0.5984 |
|
| 239 |
+
| 0.5911 | 2.11 | 191000 | 0.5953 |
|
| 240 |
+
| 0.563 | 2.13 | 192000 | 0.5772 |
|
| 241 |
+
| 0.5671 | 2.14 | 193000 | 0.5771 |
|
| 242 |
+
| 0.6051 | 2.15 | 194000 | 0.5972 |
|
| 243 |
+
| 0.5852 | 2.16 | 195000 | 0.5917 |
|
| 244 |
+
| 0.5757 | 2.17 | 196000 | 0.5819 |
|
| 245 |
+
| 0.6557 | 2.18 | 197000 | 0.5655 |
|
| 246 |
+
| 0.6055 | 2.19 | 198000 | 0.5820 |
|
| 247 |
+
| 0.6067 | 2.2 | 199000 | 0.5801 |
|
| 248 |
+
| 0.6422 | 2.21 | 200000 | 0.5590 |
|
| 249 |
+
| 0.624 | 2.23 | 201000 | 0.5573 |
|
| 250 |
+
| 0.6222 | 2.24 | 202000 | 0.5661 |
|
| 251 |
+
| 0.5597 | 2.25 | 203000 | 0.5786 |
|
| 252 |
+
| 0.5746 | 2.26 | 204000 | 0.5622 |
|
| 253 |
+
| 0.6269 | 2.27 | 205000 | 0.5804 |
|
| 254 |
+
| 0.6241 | 2.28 | 206000 | 0.5696 |
|
| 255 |
+
| 0.6519 | 2.29 | 207000 | 0.5367 |
|
| 256 |
+
| 0.6161 | 2.3 | 208000 | 0.5666 |
|
| 257 |
+
| 0.5415 | 2.31 | 209000 | 0.5633 |
|
| 258 |
+
| 0.633 | 2.33 | 210000 | 0.5499 |
|
| 259 |
+
| 0.5566 | 2.34 | 211000 | 0.5822 |
|
| 260 |
+
| 0.6158 | 2.35 | 212000 | 0.5826 |
|
| 261 |
+
| 0.5574 | 2.36 | 213000 | 0.5429 |
|
| 262 |
+
| 0.5748 | 2.37 | 214000 | 0.5736 |
|
| 263 |
+
| 0.5818 | 2.38 | 215000 | 0.5599 |
|
| 264 |
+
| 0.6226 | 2.39 | 216000 | 0.5407 |
|
| 265 |
+
| 0.5733 | 2.4 | 217000 | 0.5759 |
|
| 266 |
+
| 0.6268 | 2.41 | 218000 | 0.5725 |
|
| 267 |
+
| 0.5885 | 2.42 | 219000 | 0.5771 |
|
| 268 |
+
| 0.5708 | 2.44 | 220000 | 0.5654 |
|
| 269 |
+
| 0.5783 | 2.45 | 221000 | 0.5756 |
|
| 270 |
+
| 0.61 | 2.46 | 222000 | 0.5647 |
|
| 271 |
+
| 0.5848 | 2.47 | 223000 | 0.5532 |
|
| 272 |
+
| 0.5869 | 2.48 | 224000 | 0.5519 |
|
| 273 |
+
| 0.5717 | 2.49 | 225000 | 0.5621 |
|
| 274 |
+
| 0.5675 | 2.5 | 226000 | 0.5446 |
|
| 275 |
+
| 0.6321 | 2.51 | 227000 | 0.5812 |
|
| 276 |
+
| 0.568 | 2.52 | 228000 | 0.5673 |
|
| 277 |
+
| 0.5577 | 2.54 | 229000 | 0.5590 |
|
| 278 |
+
| 0.5888 | 2.55 | 230000 | 0.5628 |
|
| 279 |
+
| 0.6389 | 2.56 | 231000 | 0.5828 |
|
| 280 |
+
| 0.5782 | 2.57 | 232000 | 0.5543 |
|
| 281 |
+
| 0.5871 | 2.58 | 233000 | 0.5575 |
|
| 282 |
+
| 0.5593 | 2.59 | 234000 | 0.5625 |
|
| 283 |
+
| 0.6167 | 2.6 | 235000 | 0.5450 |
|
| 284 |
+
| 0.5828 | 2.61 | 236000 | 0.5627 |
|
| 285 |
+
| 0.5411 | 2.62 | 237000 | 0.5498 |
|
| 286 |
+
| 0.6168 | 2.64 | 238000 | 0.5891 |
|
| 287 |
+
| 0.6508 | 2.65 | 239000 | 0.5811 |
|
| 288 |
+
| 0.6322 | 2.66 | 240000 | 0.5649 |
|
| 289 |
+
| 0.6131 | 2.67 | 241000 | 0.5473 |
|
| 290 |
+
| 0.5419 | 2.68 | 242000 | 0.5583 |
|
| 291 |
+
| 0.5685 | 2.69 | 243000 | 0.5635 |
|
| 292 |
+
| 0.5267 | 2.7 | 244000 | 0.5481 |
|
| 293 |
+
| 0.5357 | 2.71 | 245000 | 0.5474 |
|
| 294 |
+
| 0.585 | 2.72 | 246000 | 0.5281 |
|
| 295 |
+
| 0.5894 | 2.73 | 247000 | 0.5457 |
|
| 296 |
+
| 0.5665 | 2.75 | 248000 | 0.5579 |
|
| 297 |
+
| 0.5409 | 2.76 | 249000 | 0.5412 |
|
| 298 |
+
| 0.6051 | 2.77 | 250000 | 0.5447 |
|
| 299 |
+
| 0.5866 | 2.78 | 251000 | 0.5535 |
|
| 300 |
+
| 0.5348 | 2.79 | 252000 | 0.5377 |
|
| 301 |
+
| 0.5606 | 2.8 | 253000 | 0.5524 |
|
| 302 |
+
| 0.5142 | 2.81 | 254000 | 0.5441 |
|
| 303 |
+
| 0.543 | 2.82 | 255000 | 0.5499 |
|
| 304 |
+
| 0.5763 | 2.83 | 256000 | 0.5241 |
|
| 305 |
+
|
| 306 |
+
|
| 307 |
+
### Framework versions
|
| 308 |
+
|
| 309 |
+
- Transformers 4.20.0.dev0
|
| 310 |
+
- Pytorch 1.10.0+cu102
|
| 311 |
+
- Datasets 1.15.1
|
| 312 |
+
- Tokenizers 0.11.0
|
added_tokens.json
ADDED
|
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|
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|
|
| 1 |
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{"[MASK]": 128000}
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config.json
ADDED
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@@ -0,0 +1,35 @@
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
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|
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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"_name_or_path": "models/deberta-v3-large-ddlm/checkpoint-166000",
|
| 3 |
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"architectures": [
|
| 4 |
+
"DebertaV2ForMaskedLM"
|
| 5 |
+
],
|
| 6 |
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"attention_probs_dropout_prob": 0.1,
|
| 7 |
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"hidden_act": "gelu",
|
| 8 |
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"hidden_dropout_prob": 0.1,
|
| 9 |
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"hidden_size": 1024,
|
| 10 |
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"initializer_range": 0.02,
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| 11 |
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"intermediate_size": 4096,
|
| 12 |
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"layer_norm_eps": 1e-07,
|
| 13 |
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"max_position_embeddings": 512,
|
| 14 |
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"max_relative_positions": -1,
|
| 15 |
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"model_type": "deberta-v2",
|
| 16 |
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"norm_rel_ebd": "layer_norm",
|
| 17 |
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"num_attention_heads": 16,
|
| 18 |
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"num_hidden_layers": 24,
|
| 19 |
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"pad_token_id": 0,
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| 20 |
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"pooler_dropout": 0,
|
| 21 |
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"pooler_hidden_act": "gelu",
|
| 22 |
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"pooler_hidden_size": 1024,
|
| 23 |
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"pos_att_type": [
|
| 24 |
+
"p2c",
|
| 25 |
+
"c2p"
|
| 26 |
+
],
|
| 27 |
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"position_biased_input": false,
|
| 28 |
+
"position_buckets": 256,
|
| 29 |
+
"relative_attention": true,
|
| 30 |
+
"share_att_key": true,
|
| 31 |
+
"torch_dtype": "float32",
|
| 32 |
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"transformers_version": "4.20.0.dev0",
|
| 33 |
+
"type_vocab_size": 0,
|
| 34 |
+
"vocab_size": 128001
|
| 35 |
+
}
|
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ADDED
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| 2 |
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oid sha256:b546a06c5bac92cef71cf7d0ca65735b321d9535ffa1f80cf81764762b36acf4
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| 3 |
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size 316
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scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:afc63963ca5afabe2e74f09c32eb2f23b8b37b6a3ff51e49db8094b3218c95bb
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| 3 |
+
size 623
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
|
spm.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
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|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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| 3 |
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size 2464616
|
tokenizer.json
ADDED
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|
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tokenizer_config.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"do_lower_case": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "split_by_punct": false, "sp_model_kwargs": {}, "vocab_type": "spm", "special_tokens_map_file": null, "name_or_path": "models/deberta-v3-large-ddlm/checkpoint-166000", "tokenizer_class": "DebertaV2Tokenizer"}
|
trainer_state.json
ADDED
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training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:4b9874199dc5f46d210c0e39f0b3dda226896ad2a17cfa13b24e5fa6683a92be
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| 3 |
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size 3247
|