| | --- |
| | license: mit |
| | base_model: facebook/w2v-bert-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: w2v-bert-Marathi-large |
| | 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. --> |
| |
|
| | # w2v-bert-Marathi-large |
| |
|
| | This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2714 |
| | - Wer: 0.1698 |
| | - Cer: 0.0531 |
| |
|
| | ## 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: 2 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 8 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - training_steps: 3000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| | |:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
| | | 2.8852 | 0.5882 | 300 | 0.7826 | 0.4911 | 0.1647 | |
| | | 0.6243 | 1.1765 | 600 | 0.6280 | 0.3920 | 0.1351 | |
| | | 0.4901 | 1.7647 | 900 | 0.4369 | 0.3101 | 0.0986 | |
| | | 0.355 | 2.3529 | 1200 | 0.3922 | 0.2658 | 0.0849 | |
| | | 0.2943 | 2.9412 | 1500 | 0.3400 | 0.2371 | 0.0753 | |
| | | 0.2177 | 3.5294 | 1800 | 0.3041 | 0.2080 | 0.0646 | |
| | | 0.1779 | 4.1176 | 2100 | 0.2906 | 0.1954 | 0.0608 | |
| | | 0.1299 | 4.7059 | 2400 | 0.2904 | 0.1779 | 0.0560 | |
| | | 0.0929 | 5.2941 | 2700 | 0.2885 | 0.1727 | 0.0537 | |
| | | 0.0729 | 5.8824 | 3000 | 0.2714 | 0.1698 | 0.0531 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.42.0.dev0 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| |
|
