pytorch wav2vec2 automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53_toy_train_data_fast_10pct
  results: []
---

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# wav2vec2-large-xlsr-53_toy_train_data_fast_10pct

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6983
- Wer: 0.5026

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.3619        | 1.05  | 250  | 3.4334          | 1.0    |
| 3.0818        | 2.1   | 500  | 3.4914          | 1.0    |
| 2.3245        | 3.15  | 750  | 1.6483          | 0.9486 |
| 1.0233        | 4.2   | 1000 | 0.8817          | 0.7400 |
| 0.7522        | 5.25  | 1250 | 0.7374          | 0.6529 |
| 0.5343        | 6.3   | 1500 | 0.6972          | 0.6068 |
| 0.4452        | 7.35  | 1750 | 0.6757          | 0.5740 |
| 0.4275        | 8.4   | 2000 | 0.6789          | 0.5551 |
| 0.3688        | 9.45  | 2250 | 0.6468          | 0.5394 |
| 0.3363        | 10.5  | 2500 | 0.6798          | 0.5358 |
| 0.3036        | 11.55 | 2750 | 0.6439          | 0.5265 |
| 0.3173        | 12.6  | 3000 | 0.6898          | 0.5196 |
| 0.2985        | 13.65 | 3250 | 0.6791          | 0.5169 |
| 0.288         | 14.7  | 3500 | 0.6442          | 0.5090 |
| 0.2673        | 15.75 | 3750 | 0.6984          | 0.5119 |
| 0.2575        | 16.81 | 4000 | 0.7146          | 0.5084 |
| 0.239         | 17.86 | 4250 | 0.6847          | 0.5040 |
| 0.2266        | 18.91 | 4500 | 0.6900          | 0.5028 |
| 0.22          | 19.96 | 4750 | 0.6983          | 0.5026 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu102
- Datasets 2.0.0
- Tokenizers 0.11.6
