---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: csml_word2vec
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: None
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.12267657992565056
---

<!-- 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. -->

# csml_word2vec

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2183
- Wer: 0.1227

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.2282        | 1.0   | 100  | 3.1130          | 1.0    |
| 2.9562        | 2.0   | 200  | 2.9543          | 1.0    |
| 2.9212        | 3.0   | 300  | 2.9317          | 1.0    |
| 2.9119        | 4.0   | 400  | 2.9110          | 1.0    |
| 2.9099        | 5.0   | 500  | 2.9099          | 1.0    |
| 2.9027        | 6.0   | 600  | 2.9106          | 1.0    |
| 2.4303        | 7.0   | 700  | 1.9136          | 0.9615 |
| 0.7427        | 8.0   | 800  | 0.5675          | 0.4321 |
| 0.4794        | 9.0   | 900  | 0.4161          | 0.3183 |
| 0.3372        | 10.0  | 1000 | 0.3228          | 0.2441 |
| 0.2685        | 11.0  | 1100 | 0.2762          | 0.1916 |
| 0.2092        | 12.0  | 1200 | 0.2522          | 0.1654 |
| 0.1848        | 13.0  | 1300 | 0.2361          | 0.1564 |
| 0.1678        | 14.0  | 1400 | 0.2246          | 0.1383 |
| 0.1377        | 15.0  | 1500 | 0.2183          | 0.1337 |
| 0.122         | 16.0  | 1600 | 0.2206          | 0.1310 |
| 0.1125        | 17.0  | 1700 | 0.2205          | 0.1285 |
| 0.0938        | 18.0  | 1800 | 0.2219          | 0.1273 |
| 0.0994        | 19.0  | 1900 | 0.2209          | 0.1239 |
| 0.1           | 20.0  | 2000 | 0.2183          | 0.1227 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1