---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 240626-wav2vec2-ASR_Global
  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. -->

# 240626-wav2vec2-ASR_Global

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4971
- Wer: 0.0966

## 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: 5e-05
- train_batch_size: 5
- 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| No log        | 1.4085  | 100  | 0.5435          | 0.1003 |
| No log        | 2.8169  | 200  | 0.5230          | 0.1092 |
| No log        | 4.2254  | 300  | 0.5379          | 0.1105 |
| No log        | 5.6338  | 400  | 0.5906          | 0.1244 |
| 0.1133        | 7.0423  | 500  | 0.5424          | 0.1148 |
| 0.1133        | 8.4507  | 600  | 0.5311          | 0.1318 |
| 0.1133        | 9.8592  | 700  | 0.5263          | 0.12   |
| 0.1133        | 11.2676 | 800  | 0.5259          | 0.1123 |
| 0.1133        | 12.6761 | 900  | 0.5031          | 0.1030 |
| 0.128         | 14.0845 | 1000 | 0.5482          | 0.1103 |
| 0.128         | 15.4930 | 1100 | 0.5225          | 0.1038 |
| 0.128         | 16.9014 | 1200 | 0.4823          | 0.0980 |
| 0.128         | 18.3099 | 1300 | 0.4971          | 0.0966 |
| 0.128         | 19.7183 | 1400 | 0.5219          | 0.0982 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1