metadata
base_model: NousResearch/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: classifier-7b-v9
results: []
classifier-7b-v9
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8197
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.171 | 0.02 | 20 | 2.1160 |
| 1.881 | 0.04 | 40 | 1.9814 |
| 2.0141 | 0.06 | 60 | 1.9357 |
| 1.9386 | 0.08 | 80 | 1.9156 |
| 1.9899 | 0.1 | 100 | 1.9032 |
| 1.9022 | 0.11 | 120 | 1.8964 |
| 1.9176 | 0.13 | 140 | 1.8880 |
| 1.9431 | 0.15 | 160 | 1.8827 |
| 1.8847 | 0.17 | 180 | 1.8772 |
| 1.8158 | 0.19 | 200 | 1.8740 |
| 1.851 | 0.21 | 220 | 1.8711 |
| 1.8173 | 0.23 | 240 | 1.8678 |
| 1.7902 | 0.25 | 260 | 1.8639 |
| 1.8507 | 0.27 | 280 | 1.8600 |
| 1.8749 | 0.29 | 300 | 1.8582 |
| 1.9203 | 0.3 | 320 | 1.8543 |
| 1.8876 | 0.32 | 340 | 1.8518 |
| 1.8918 | 0.34 | 360 | 1.8510 |
| 1.9568 | 0.36 | 380 | 1.8482 |
| 1.7887 | 0.38 | 400 | 1.8489 |
| 1.9188 | 0.4 | 420 | 1.8451 |
| 1.855 | 0.42 | 440 | 1.8434 |
| 1.94 | 0.44 | 460 | 1.8421 |
| 1.7969 | 0.46 | 480 | 1.8399 |
| 1.875 | 0.48 | 500 | 1.8384 |
| 1.8493 | 0.5 | 520 | 1.8383 |
| 1.8048 | 0.51 | 540 | 1.8370 |
| 1.9077 | 0.53 | 560 | 1.8352 |
| 1.804 | 0.55 | 580 | 1.8327 |
| 1.8623 | 0.57 | 600 | 1.8315 |
| 1.8156 | 0.59 | 620 | 1.8312 |
| 1.8639 | 0.61 | 640 | 1.8306 |
| 1.909 | 0.63 | 660 | 1.8292 |
| 1.8636 | 0.65 | 680 | 1.8290 |
| 1.7888 | 0.67 | 700 | 1.8270 |
| 1.7797 | 0.69 | 720 | 1.8259 |
| 1.8014 | 0.7 | 740 | 1.8248 |
| 1.7313 | 0.72 | 760 | 1.8240 |
| 1.8429 | 0.74 | 780 | 1.8235 |
| 1.814 | 0.76 | 800 | 1.8235 |
| 1.7861 | 0.78 | 820 | 1.8221 |
| 1.8515 | 0.8 | 840 | 1.8212 |
| 1.8432 | 0.82 | 860 | 1.8209 |
| 1.8018 | 0.84 | 880 | 1.8204 |
| 1.864 | 0.86 | 900 | 1.8203 |
| 1.7234 | 0.88 | 920 | 1.8201 |
| 1.84 | 0.89 | 940 | 1.8198 |
| 1.8721 | 0.91 | 960 | 1.8199 |
| 1.7822 | 0.93 | 980 | 1.8198 |
| 1.8464 | 0.95 | 1000 | 1.8197 |
| 1.7454 | 0.97 | 1020 | 1.8197 |
| 1.7434 | 0.99 | 1040 | 1.8197 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1