metadata
license: apache-2.0
base_model: facebook/bart-large
tags:
- text2text-generation
- generated_from_trainer
metrics:
- sacrebleu
model-index:
- name: model_v3_v2
results: []
model_v3_v2
This model is a fine-tuned version of facebook/bart-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1977
- Sacrebleu: 66.7256
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|---|---|---|---|---|
| No log | 0.99 | 54 | 0.5648 | 65.7974 |
| No log | 1.99 | 109 | 0.6224 | 66.8854 |
| No log | 3.0 | 164 | 0.6639 | 66.8333 |
| No log | 4.0 | 219 | 0.5929 | 66.7857 |
| No log | 4.99 | 273 | 0.6427 | 65.8395 |
| No log | 5.99 | 328 | 0.6721 | 66.4172 |
| No log | 7.0 | 383 | 0.7511 | 66.4660 |
| No log | 8.0 | 438 | 0.7662 | 66.6480 |
| No log | 8.99 | 492 | 0.7588 | 66.5092 |
| No log | 9.99 | 547 | 0.7916 | 66.5144 |
| No log | 11.0 | 602 | 0.8172 | 66.6279 |
| No log | 12.0 | 657 | 0.8350 | 66.5607 |
| No log | 12.99 | 711 | 0.8809 | 66.6095 |
| No log | 13.99 | 766 | 0.8843 | 66.4089 |
| No log | 15.0 | 821 | 1.0130 | 66.5184 |
| No log | 16.0 | 876 | 0.9180 | 66.4269 |
| No log | 16.99 | 930 | 0.9794 | 66.5766 |
| No log | 17.99 | 985 | 0.9450 | 66.6713 |
| No log | 19.0 | 1040 | 0.9880 | 66.7081 |
| No log | 20.0 | 1095 | 0.9540 | 66.4440 |
| No log | 20.99 | 1149 | 1.0552 | 66.5390 |
| No log | 21.99 | 1204 | 0.9806 | 66.5975 |
| No log | 23.0 | 1259 | 1.0528 | 66.6404 |
| No log | 24.0 | 1314 | 1.0348 | 66.4127 |
| No log | 24.99 | 1368 | 1.0758 | 66.6139 |
| No log | 25.99 | 1423 | 1.1291 | 66.6778 |
| No log | 27.0 | 1478 | 1.1112 | 66.6411 |
| No log | 28.0 | 1533 | 1.1305 | 66.5986 |
| No log | 28.99 | 1587 | 1.1532 | 66.5047 |
| No log | 29.99 | 1642 | 1.1106 | 66.5662 |
| No log | 31.0 | 1697 | 1.2084 | 66.6593 |
| No log | 32.0 | 1752 | 1.1438 | 66.6117 |
| No log | 32.99 | 1806 | 1.1956 | 66.6758 |
| No log | 33.99 | 1861 | 1.1630 | 66.7359 |
| No log | 35.0 | 1916 | 1.1570 | 66.6989 |
| No log | 36.0 | 1971 | 1.1754 | 66.6495 |
| No log | 36.99 | 2025 | 1.2456 | 66.7018 |
| No log | 37.99 | 2080 | 1.2197 | 66.7990 |
| No log | 39.0 | 2135 | 1.1886 | 66.7049 |
| No log | 39.45 | 2160 | 1.1977 | 66.7256 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2