model_v1_complete_training_wt_init_48_small_emb_comp_frz
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.0873
- Accuracy: 0.3585
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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.1895 | 0.25 | 30000 | 6.1896 | 0.1440 |
| 6.142 | 0.49 | 60000 | 6.1411 | 0.1464 |
| 6.1111 | 0.74 | 90000 | 6.1027 | 0.1482 |
| 6.0564 | 0.98 | 120000 | 6.0542 | 0.1499 |
| 6.0105 | 1.23 | 150000 | 5.9999 | 0.1525 |
| 5.9542 | 1.47 | 180000 | 5.9441 | 0.1555 |
| 5.8828 | 1.72 | 210000 | 5.8687 | 0.1602 |
| 5.8099 | 1.97 | 240000 | 5.7963 | 0.1680 |
| 5.7234 | 2.21 | 270000 | 5.6868 | 0.1851 |
| 5.4249 | 2.46 | 300000 | 5.3582 | 0.2278 |
| 5.0172 | 2.7 | 330000 | 4.9641 | 0.2721 |
| 4.7387 | 2.95 | 360000 | 4.6970 | 0.2991 |
| 4.5625 | 3.2 | 390000 | 4.5123 | 0.3164 |
| 4.4301 | 3.44 | 420000 | 4.3802 | 0.3295 |
| 4.3369 | 3.69 | 450000 | 4.2827 | 0.3389 |
| 4.2632 | 3.93 | 480000 | 4.2126 | 0.3459 |
| 4.2074 | 4.18 | 510000 | 4.1586 | 0.3516 |
| 4.1713 | 4.42 | 540000 | 4.1218 | 0.3551 |
| 4.1448 | 4.67 | 570000 | 4.0984 | 0.3573 |
| 4.1356 | 4.92 | 600000 | 4.0873 | 0.3585 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3