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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-finetuned-ie |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-base-finetuned-ie |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0066 |
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- Accuracy: 0.6487 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.1544 | 1.0 | 102 | 1.1369 | 0.5063 | |
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| 1.0574 | 2.0 | 204 | 1.0677 | 0.5121 | |
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| 0.8303 | 3.0 | 306 | 0.9213 | 0.6091 | |
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| 0.7753 | 4.0 | 408 | 1.0430 | 0.5926 | |
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| 0.6142 | 5.0 | 510 | 1.1218 | 0.6033 | |
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| 0.5152 | 6.0 | 612 | 1.1629 | 0.6188 | |
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| 0.51 | 7.0 | 714 | 0.9371 | 0.6838 | |
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| 0.2368 | 8.0 | 816 | 1.2314 | 0.6343 | |
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| 0.2315 | 9.0 | 918 | 1.3838 | 0.6285 | |
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| 0.2324 | 10.0 | 1020 | 1.3675 | 0.6489 | |
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| 0.1919 | 11.0 | 1122 | 1.5164 | 0.6372 | |
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| 0.0962 | 12.0 | 1224 | 1.5281 | 0.6440 | |
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| 0.0851 | 13.0 | 1326 | 1.5718 | 0.6479 | |
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| 0.0358 | 14.0 | 1428 | 1.6729 | 0.6508 | |
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| 0.0754 | 15.0 | 1530 | 1.6681 | 0.6528 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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