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---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vecvanilla_ctc_zero_infinity_longertrain
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. -->
# wav2vecvanilla_ctc_zero_infinity_longertrain
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1396
- Wer: 0.2973
## 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: 4
- 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: 500
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.4721 | 0.43 | 100 | 1.0565 | 0.4014 |
| 1.2574 | 0.85 | 200 | 0.9707 | 0.3704 |
| 1.1397 | 1.28 | 300 | 0.9644 | 0.3609 |
| 1.0939 | 1.71 | 400 | 0.9610 | 0.3637 |
| 1.0874 | 2.14 | 500 | 0.9508 | 0.3581 |
| 1.0573 | 2.56 | 600 | 0.8865 | 0.3518 |
| 1.0386 | 2.99 | 700 | 1.0304 | 0.3493 |
| 0.9792 | 3.42 | 800 | 0.8235 | 0.3523 |
| 0.9789 | 3.85 | 900 | 0.8404 | 0.3388 |
| 0.9095 | 4.27 | 1000 | 1.0925 | 0.3588 |
| 0.8947 | 4.7 | 1100 | 1.0126 | 0.3357 |
| 0.8571 | 5.13 | 1200 | 1.1404 | 0.3550 |
| 0.8276 | 5.56 | 1300 | 0.8135 | 0.3294 |
| 0.8631 | 5.98 | 1400 | 0.8342 | 0.3279 |
| 0.8134 | 6.41 | 1500 | 0.8524 | 0.3177 |
| 0.8027 | 6.84 | 1600 | 0.8182 | 0.3207 |
| 0.7556 | 7.26 | 1700 | 0.8445 | 0.3185 |
| 0.737 | 7.69 | 1800 | 0.8919 | 0.3197 |
| 0.7398 | 8.12 | 1900 | 0.8115 | 0.3167 |
| 0.7069 | 8.55 | 2000 | 0.8346 | 0.3174 |
| 0.7206 | 8.97 | 2100 | 0.9714 | 0.3147 |
| 0.6946 | 9.4 | 2200 | 0.8138 | 0.3124 |
| 0.6752 | 9.83 | 2300 | 0.8366 | 0.3086 |
| 0.7256 | 10.26 | 2400 | 0.8482 | 0.3044 |
| 0.7063 | 10.68 | 2500 | 0.8997 | 0.3041 |
| 0.6399 | 11.11 | 2600 | 0.8614 | 0.3045 |
| 0.6268 | 11.54 | 2700 | 0.8564 | 0.3018 |
| 0.6665 | 11.97 | 2800 | 0.8531 | 0.3006 |
| 0.622 | 12.39 | 2900 | 0.8759 | 0.3007 |
| 0.6568 | 12.82 | 3000 | 1.3093 | 0.3023 |
| 0.6296 | 13.25 | 3100 | 1.1312 | 0.3002 |
| 0.6448 | 13.68 | 3200 | 1.1779 | 0.2994 |
| 0.6188 | 14.1 | 3300 | 1.1203 | 0.2989 |
| 0.6216 | 14.53 | 3400 | 1.1421 | 0.2978 |
| 0.6238 | 14.96 | 3500 | 1.1396 | 0.2973 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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