<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
Bert_large_14ep_mimic
This model is a fine-tuned version of alecocc/bert_large_top10 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4463
- Precision Macro: 0.3048
- Recall Macro: 0.3196
- F1 Macro: 0.3073
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Recall Macro | F1 Macro |
|---|---|---|---|---|---|---|
| 0.5133 | 1.0 | 1925 | 0.4229 | 0.4001 | 0.2679 | 0.2545 |
| 0.5274 | 2.0 | 3850 | 0.4367 | 0.2443 | 0.2382 | 0.2345 |
| 0.4361 | 3.0 | 5775 | 0.4419 | 0.2986 | 0.2925 | 0.2764 |
| 0.3229 | 4.0 | 7700 | 0.4463 | 0.3048 | 0.3196 | 0.3073 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6.dev0
- Tokenizers 0.14.0
