| | --- |
| | license: mit |
| | base_model: microsoft/deberta-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: deberta_large_finetuned_claimdecomp |
| | 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. --> |
| |
|
| | # deberta_large_finetuned_claimdecomp |
| | |
| | This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.7614 |
| | - Accuracy: 0.205 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - training_steps: 30000 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 1.7304 | 50.0 | 5000 | 1.7493 | 0.255 | |
| | | 1.7282 | 100.0 | 10000 | 1.7495 | 0.205 | |
| | | 1.7196 | 150.0 | 15000 | 1.7457 | 0.255 | |
| | | 1.7107 | 200.0 | 20000 | 1.7462 | 0.255 | |
| | | 1.7107 | 250.0 | 25000 | 1.7666 | 0.205 | |
| | | 1.6992 | 300.0 | 30000 | 1.7614 | 0.205 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.34.1 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| | |
