| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: output_mlm |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # output_mlm |
| | |
| | This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2024 |
| | |
| | ## 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: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:------:|:---------------:| |
| | | 1.5832 | 0.19 | 15000 | 1.4992 | |
| | | 1.5325 | 0.39 | 30000 | 1.4653 | |
| | | 1.4979 | 0.58 | 45000 | 1.4359 | |
| | | 1.4715 | 0.77 | 60000 | 1.4039 | |
| | | 1.4448 | 0.97 | 75000 | 1.3877 | |
| | | 1.4191 | 1.16 | 90000 | 1.3603 | |
| | | 1.3988 | 1.35 | 105000 | 1.3425 | |
| | | 1.3699 | 1.54 | 120000 | 1.3230 | |
| | | 1.3493 | 1.74 | 135000 | 1.3012 | |
| | | 1.3201 | 1.93 | 150000 | 1.2773 | |
| | | 1.2993 | 2.12 | 165000 | 1.2617 | |
| | | 1.2745 | 2.32 | 180000 | 1.2490 | |
| | | 1.2614 | 2.51 | 195000 | 1.2283 | |
| | | 1.2424 | 2.7 | 210000 | 1.2152 | |
| | | 1.2296 | 2.9 | 225000 | 1.2052 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.11.2 |
| | - Pytorch 1.9.0 |
| | - Datasets 1.12.1 |
| | - Tokenizers 0.10.3 |
| |
|
