---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- wer
model-index:
- name: wav2vec2-minds14-en
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: minds14
      type: minds14
      config: en-US
      split: None
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 1.0
---

<!-- 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-minds14-en

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5729
- Wer: 1.0

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.3811        | 3.5088  | 100  | 6.8598          | 1.0006 |
| 4.9442        | 7.0175  | 200  | 6.6217          | 1.0018 |
| 4.6255        | 10.5263 | 300  | 6.2050          | 1.0    |
| 4.4037        | 14.0351 | 400  | 6.1160          | 1.0    |
| 4.1672        | 17.5439 | 500  | 5.7863          | 1.0    |
| 3.8786        | 21.0526 | 600  | 5.6219          | 1.0    |
| 3.6182        | 24.5614 | 700  | 5.4987          | 1.0    |
| 3.654         | 28.0702 | 800  | 5.6024          | 1.0    |
| 3.4135        | 31.5789 | 900  | 5.5648          | 1.0    |
| 3.3532        | 35.0877 | 1000 | 5.6507          | 1.0    |
| 3.344         | 38.5965 | 1100 | 5.5189          | 1.0    |
| 3.3233        | 42.1053 | 1200 | 5.6830          | 1.0    |
| 3.3983        | 45.6140 | 1300 | 5.5447          | 1.0    |
| 3.2433        | 49.1228 | 1400 | 5.5065          | 1.0    |
| 3.2082        | 52.6316 | 1500 | 5.4783          | 1.0    |
| 3.1958        | 56.1404 | 1600 | 5.5747          | 1.0    |
| 3.1756        | 59.6491 | 1700 | 5.5580          | 1.0    |
| 3.1757        | 63.1579 | 1800 | 5.5556          | 1.0    |
| 3.1758        | 66.6667 | 1900 | 5.6747          | 1.0    |
| 3.1373        | 70.1754 | 2000 | 5.5729          | 1.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1