---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wtimit-base-960h-normal30percent-all
  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. -->

# wtimit-base-960h-normal30percent-all

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: 0.8097
- Wer: 0.3692

## 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: 8
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 0.32          | 1.3889  | 1000  | 0.3506          | 0.2804 |
| 0.2342        | 2.7778  | 2000  | 0.4413          | 0.2977 |
| 0.183         | 4.1667  | 3000  | 0.4847          | 0.3134 |
| 0.1389        | 5.5556  | 4000  | 0.5576          | 0.3291 |
| 0.1156        | 6.9444  | 5000  | 0.6021          | 0.3405 |
| 0.1003        | 8.3333  | 6000  | 0.6778          | 0.3632 |
| 0.0921        | 9.7222  | 7000  | 0.6309          | 0.3549 |
| 0.0771        | 11.1111 | 8000  | 0.7765          | 0.3823 |
| 0.0674        | 12.5    | 9000  | 0.7512          | 0.3722 |
| 0.0629        | 13.8889 | 10000 | 0.6964          | 0.3764 |
| 0.0575        | 15.2778 | 11000 | 0.8090          | 0.3812 |
| 0.0531        | 16.6667 | 12000 | 0.8377          | 0.3919 |
| 0.044         | 18.0556 | 13000 | 0.8246          | 0.3881 |
| 0.0427        | 19.4444 | 14000 | 0.8331          | 0.3826 |
| 0.0415        | 20.8333 | 15000 | 0.8166          | 0.3800 |
| 0.0356        | 22.2222 | 16000 | 0.8550          | 0.3916 |
| 0.0359        | 23.6111 | 17000 | 0.7968          | 0.3843 |
| 0.0311        | 25.0    | 18000 | 0.8020          | 0.3788 |
| 0.0251        | 26.3889 | 19000 | 0.8026          | 0.3684 |
| 0.0264        | 27.7778 | 20000 | 0.7937          | 0.3743 |
| 0.0248        | 29.1667 | 21000 | 0.8097          | 0.3692 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1