---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-960h-finetuned-asr-PolyAI_minds14-en-US
  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-960h-finetuned-asr-PolyAI_minds14-en-US

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6485
- Wer: 0.3319

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 125
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.5518        | 12.4  | 62   | 1.5976          | 0.4723 |
| 1.0477        | 24.8  | 124  | 1.1343          | 0.3617 |
| 0.7908        | 37.2  | 186  | 1.5092          | 0.3447 |
| 0.6269        | 49.6  | 248  | 1.5146          | 0.3617 |
| 0.5075        | 62.0  | 310  | 1.4677          | 0.3574 |
| 0.4534        | 74.4  | 372  | 1.5825          | 0.3191 |
| 0.4621        | 86.8  | 434  | 1.6253          | 0.3191 |
| 0.4314        | 99.2  | 496  | 1.6485          | 0.3319 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1