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---
license: apache-2.0
tags:
- generated_from_trainer
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: 0.5255
- Wer: 0.3330
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5942 | 1.0 | 500 | 2.3849 | 1.0011 |
| 0.9765 | 2.01 | 1000 | 0.5907 | 0.5202 |
| 0.4424 | 3.01 | 1500 | 0.4547 | 0.4661 |
| 0.3008 | 4.02 | 2000 | 0.4194 | 0.4228 |
| 0.2316 | 5.02 | 2500 | 0.3933 | 0.4099 |
| 0.1921 | 6.02 | 3000 | 0.4532 | 0.3965 |
| 0.1561 | 7.03 | 3500 | 0.4315 | 0.3777 |
| 0.1378 | 8.03 | 4000 | 0.4463 | 0.3847 |
| 0.1222 | 9.04 | 4500 | 0.4402 | 0.3784 |
| 0.1076 | 10.04 | 5000 | 0.4253 | 0.3735 |
| 0.0924 | 11.04 | 5500 | 0.4844 | 0.3732 |
| 0.0866 | 12.05 | 6000 | 0.4758 | 0.3646 |
| 0.086 | 13.05 | 6500 | 0.6395 | 0.4594 |
| 0.0763 | 14.06 | 7000 | 0.4951 | 0.3647 |
| 0.0684 | 15.06 | 7500 | 0.4870 | 0.3577 |
| 0.0616 | 16.06 | 8000 | 0.5442 | 0.3591 |
| 0.0594 | 17.07 | 8500 | 0.5305 | 0.3606 |
| 0.0613 | 18.07 | 9000 | 0.5434 | 0.3546 |
| 0.0473 | 19.08 | 9500 | 0.4818 | 0.3532 |
| 0.0463 | 20.08 | 10000 | 0.5086 | 0.3514 |
| 0.042 | 21.08 | 10500 | 0.5017 | 0.3484 |
| 0.0365 | 22.09 | 11000 | 0.5129 | 0.3536 |
| 0.0336 | 23.09 | 11500 | 0.5411 | 0.3433 |
| 0.0325 | 24.1 | 12000 | 0.5307 | 0.3424 |
| 0.0282 | 25.1 | 12500 | 0.5261 | 0.3404 |
| 0.0245 | 26.1 | 13000 | 0.5306 | 0.3388 |
| 0.0257 | 27.11 | 13500 | 0.5242 | 0.3369 |
| 0.0234 | 28.11 | 14000 | 0.5216 | 0.3359 |
| 0.0221 | 29.12 | 14500 | 0.5255 | 0.3330 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
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