| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: addison6 |
| | 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. --> |
| |
|
| | # addison6 |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.4278 |
| | - Wer: 0.3784 |
| |
|
| | ## 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: 0.0001 |
| | - 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 |
| | - lr_scheduler_warmup_steps: 1000 |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:| |
| | | 4.0707 | 1.03 | 500 | 2.8972 | 0.9998 | |
| | | 1.8869 | 2.05 | 1000 | 1.3286 | 0.6772 | |
| | | 1.218 | 3.08 | 1500 | 1.0999 | 0.5714 | |
| | | 1.0183 | 4.11 | 2000 | 1.0781 | 0.5523 | |
| | | 0.8743 | 5.13 | 2500 | 0.9991 | 0.4951 | |
| | | 0.7561 | 6.16 | 3000 | 1.0861 | 0.4869 | |
| | | 0.6883 | 7.19 | 3500 | 1.1915 | 0.4704 | |
| | | 0.6185 | 8.21 | 4000 | 1.1553 | 0.4634 | |
| | | 0.5761 | 9.24 | 4500 | 1.1144 | 0.4513 | |
| | | 0.5315 | 10.27 | 5000 | 1.1818 | 0.4298 | |
| | | 0.4982 | 11.29 | 5500 | 1.1973 | 0.4329 | |
| | | 0.4719 | 12.32 | 6000 | 1.1456 | 0.4259 | |
| | | 0.4369 | 13.35 | 6500 | 1.1701 | 0.4292 | |
| | | 0.4083 | 14.37 | 7000 | 1.1929 | 0.4132 | |
| | | 0.3886 | 15.4 | 7500 | 1.3307 | 0.4163 | |
| | | 0.3752 | 16.43 | 8000 | 1.3405 | 0.4081 | |
| | | 0.349 | 17.45 | 8500 | 1.3283 | 0.3952 | |
| | | 0.3261 | 18.48 | 9000 | 1.2956 | 0.4128 | |
| | | 0.3094 | 19.51 | 9500 | 1.2671 | 0.4004 | |
| | | 0.3041 | 20.53 | 10000 | 1.3534 | 0.3964 | |
| | | 0.2796 | 21.56 | 10500 | 1.3730 | 0.3899 | |
| | | 0.25 | 22.59 | 11000 | 1.3952 | 0.3942 | |
| | | 0.2303 | 23.61 | 11500 | 1.4792 | 0.3923 | |
| | | 0.2321 | 24.64 | 12000 | 1.4228 | 0.3847 | |
| | | 0.2 | 25.67 | 12500 | 1.4469 | 0.3837 | |
| | | 0.2009 | 26.69 | 13000 | 1.4532 | 0.3820 | |
| | | 0.195 | 27.72 | 13500 | 1.4329 | 0.3821 | |
| | | 0.1804 | 28.75 | 14000 | 1.4265 | 0.3799 | |
| | | 0.1713 | 29.77 | 14500 | 1.4278 | 0.3784 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.13.2 |
| | |
