transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: model_wav2vec_
  results: []
---

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# model_wav2vec_

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: 0.4608
- Wer: 0.3361

## 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: 16
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.5101        | 2.01  | 500  | 1.6030          | 1.0221 |
| 0.7158        | 4.02  | 1000 | 0.4599          | 0.4587 |
| 0.2914        | 6.02  | 1500 | 0.4092          | 0.4037 |
| 0.1906        | 8.03  | 2000 | 0.3927          | 0.3865 |
| 0.1328        | 10.04 | 2500 | 0.4067          | 0.3810 |
| 0.1122        | 12.05 | 3000 | 0.4128          | 0.3645 |
| 0.0954        | 14.06 | 3500 | 0.4469          | 0.3621 |
| 0.0754        | 16.06 | 4000 | 0.4296          | 0.3639 |
| 0.0589        | 18.07 | 4500 | 0.4434          | 0.3567 |
| 0.0497        | 20.08 | 5000 | 0.4597          | 0.3535 |
| 0.0455        | 22.09 | 5500 | 0.4854          | 0.3454 |
| 0.0395        | 24.1  | 6000 | 0.4615          | 0.3435 |
| 0.0328        | 26.1  | 6500 | 0.4714          | 0.3396 |
| 0.0284        | 28.11 | 7000 | 0.4608          | 0.3361 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 1.18.3
- Tokenizers 0.15.0
