| | --- |
| | language: |
| | - en |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: SEED0042 |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: MNLI |
| | type: '' |
| | args: mnli |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.8879266428935303 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # SEED0042 |
| |
|
| | This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the MNLI dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4265 |
| | - Accuracy: 0.8879 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - distributed_type: not_parallel |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 2000 |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.3762 | 1.0 | 12272 | 0.3312 | 0.8794 | |
| | | 0.2542 | 2.0 | 24544 | 0.3467 | 0.8843 | |
| | | 0.1503 | 3.0 | 36816 | 0.4265 | 0.8879 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0 |
| | - Pytorch 1.10.0+cu113 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.11.6 |
| | |
