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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: 0.5353
- Wer: 0.3360
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5345 | 1.0 | 500 | 1.8229 | 0.9810 |
| 0.8731 | 2.01 | 1000 | 0.5186 | 0.5165 |
| 0.4455 | 3.01 | 1500 | 0.4386 | 0.4572 |
| 0.3054 | 4.02 | 2000 | 0.4396 | 0.4286 |
| 0.2354 | 5.02 | 2500 | 0.4454 | 0.4051 |
| 0.1897 | 6.02 | 3000 | 0.4465 | 0.3925 |
| 0.1605 | 7.03 | 3500 | 0.4776 | 0.3974 |
| 0.1413 | 8.03 | 4000 | 0.5254 | 0.4062 |
| 0.1211 | 9.04 | 4500 | 0.5123 | 0.3913 |
| 0.1095 | 10.04 | 5000 | 0.4171 | 0.3711 |
| 0.1039 | 11.04 | 5500 | 0.4258 | 0.3732 |
| 0.0932 | 12.05 | 6000 | 0.4879 | 0.3701 |
| 0.0867 | 13.05 | 6500 | 0.4725 | 0.3637 |
| 0.0764 | 14.06 | 7000 | 0.5041 | 0.3636 |
| 0.0661 | 15.06 | 7500 | 0.4692 | 0.3646 |
| 0.0647 | 16.06 | 8000 | 0.4804 | 0.3612 |
| 0.0576 | 17.07 | 8500 | 0.5545 | 0.3628 |
| 0.0577 | 18.07 | 9000 | 0.5004 | 0.3557 |
| 0.0481 | 19.08 | 9500 | 0.5341 | 0.3558 |
| 0.0466 | 20.08 | 10000 | 0.5056 | 0.3514 |
| 0.0433 | 21.08 | 10500 | 0.4864 | 0.3481 |
| 0.0362 | 22.09 | 11000 | 0.4994 | 0.3473 |
| 0.0325 | 23.09 | 11500 | 0.5327 | 0.3446 |
| 0.0351 | 24.1 | 12000 | 0.5360 | 0.3445 |
| 0.0284 | 25.1 | 12500 | 0.5085 | 0.3399 |
| 0.027 | 26.1 | 13000 | 0.5344 | 0.3426 |
| 0.0247 | 27.11 | 13500 | 0.5310 | 0.3357 |
| 0.0251 | 28.11 | 14000 | 0.5201 | 0.3355 |
| 0.0228 | 29.12 | 14500 | 0.5353 | 0.3360 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
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