---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-960h-fine-tuning
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ashe194-700/facebook-wav-2-vec-fine-tuning/runs/vqwjvpmo)
# wav2vec2-960h-fine-tuning

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.8952
- Wer: 99.9699

## 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: 32
- eval_batch_size: 16
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 15.6622       | 0.6536 | 100  | 56.5642         | 99.9699 |
| 9.4272        | 1.3072 | 200  | 8.8586          | 99.9699 |
| 4.5296        | 1.9608 | 300  | 5.3600          | 99.9699 |
| 3.4224        | 2.6144 | 400  | 5.8952          | 99.9699 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1