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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-timit-demo-google-colab
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. -->
# wav2vec2-base-timit-demo-google-colab
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: 3.0392
- Wer: 1.0
## 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: 0.001
- 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: 400
- num_epochs: 150
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 5.2993 | 8.0 | 200 | 3.0327 | 1.0 |
| 3.0806 | 16.0 | 400 | 3.0476 | 1.0 |
| 3.0219 | 24.0 | 600 | 3.0472 | 1.0 |
| 3.0179 | 32.0 | 800 | 3.0435 | 1.0 |
| 3.0157 | 40.0 | 1000 | 3.0546 | 1.0 |
| 3.0146 | 48.0 | 1200 | 3.0484 | 1.0 |
| 3.0139 | 56.0 | 1400 | 3.0344 | 1.0 |
| 3.0118 | 64.0 | 1600 | 3.0351 | 1.0 |
| 3.0114 | 72.0 | 1800 | 3.0559 | 1.0 |
| 3.0114 | 80.0 | 2000 | 3.0526 | 1.0 |
| 3.0108 | 88.0 | 2200 | 3.0417 | 1.0 |
| 3.0092 | 96.0 | 2400 | 3.0629 | 1.0 |
| 3.0089 | 104.0 | 2600 | 3.0352 | 1.0 |
| 3.0083 | 112.0 | 2800 | 3.0503 | 1.0 |
| 3.0078 | 120.0 | 3000 | 3.0529 | 1.0 |
| 3.0072 | 128.0 | 3200 | 3.0378 | 1.0 |
| 3.0068 | 136.0 | 3400 | 3.0481 | 1.0 |
| 3.0063 | 144.0 | 3600 | 3.0392 | 1.0 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3
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