---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: JP-base-clean-0215
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.983
---

<!-- 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. -->

# JP-base-clean-0215

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0988
- Wer: 0.983

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 3125.0
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer   |
|:-------------:|:-----:|:-----:|:---------------:|:-----:|
| 5.5004        | 1.0   | 625   | 7.2647          | 1.0   |
| 4.0716        | 2.0   | 1250  | 4.3871          | 1.0   |
| 3.3302        | 3.0   | 1875  | 3.1038          | 1.0   |
| 0.8423        | 4.0   | 2500  | 0.9833          | 0.998 |
| 0.5152        | 5.0   | 3125  | 0.7318          | 0.996 |
| 0.3984        | 6.0   | 3750  | 0.4784          | 0.996 |
| 0.3481        | 7.0   | 4375  | 0.3688          | 0.994 |
| 0.3149        | 8.0   | 5000  | 0.3821          | 0.994 |
| 0.2852        | 9.0   | 5625  | 0.2320          | 0.992 |
| 0.2576        | 10.0  | 6250  | 0.2887          | 0.991 |
| 0.2423        | 11.0  | 6875  | 0.2071          | 0.991 |
| 0.2278        | 12.0  | 7500  | 0.1700          | 0.989 |
| 0.2104        | 13.0  | 8125  | 0.1553          | 0.991 |
| 0.2016        | 14.0  | 8750  | 0.1500          | 0.988 |
| 0.1967        | 15.0  | 9375  | 0.1357          | 0.985 |
| 0.1838        | 16.0  | 10000 | 0.1615          | 0.988 |
| 0.172         | 17.0  | 10625 | 0.1238          | 0.986 |
| 0.1687        | 18.0  | 11250 | 0.1270          | 0.988 |
| 0.1555        | 19.0  | 11875 | 0.1221          | 0.987 |
| 0.1532        | 20.0  | 12500 | 0.1168          | 0.988 |
| 0.1414        | 21.0  | 13125 | 0.1175          | 0.988 |
| 0.1366        | 22.0  | 13750 | 0.1231          | 0.985 |
| 0.1341        | 23.0  | 14375 | 0.1004          | 0.987 |
| 0.1273        | 24.0  | 15000 | 0.1175          | 0.984 |
| 0.1199        | 25.0  | 15625 | 0.1246          | 0.984 |
| 0.1181        | 26.0  | 16250 | 0.1382          | 0.985 |
| 0.1152        | 27.0  | 16875 | 0.1064          | 0.984 |
| 0.1116        | 28.0  | 17500 | 0.1075          | 0.985 |
| 0.1097        | 29.0  | 18125 | 0.1110          | 0.986 |
| 0.1074        | 30.0  | 18750 | 0.1399          | 0.983 |
| 0.0997        | 31.0  | 19375 | 0.1385          | 0.983 |
| 0.0998        | 32.0  | 20000 | 0.1185          | 0.983 |
| 0.0973        | 33.0  | 20625 | 0.1491          | 0.982 |
| 0.0988        | 34.0  | 21250 | 0.1232          | 0.983 |
| 0.0942        | 35.0  | 21875 | 0.1205          | 0.98  |
| 0.0949        | 36.0  | 22500 | 0.1109          | 0.981 |
| 0.0947        | 37.0  | 23125 | 0.1119          | 0.982 |
| 0.0939        | 38.0  | 23750 | 0.1151          | 0.983 |
| 0.0876        | 39.0  | 24375 | 0.1001          | 0.982 |
| 0.0893        | 40.0  | 25000 | 0.0957          | 0.984 |
| 0.0897        | 41.0  | 25625 | 0.0924          | 0.982 |
| 0.0859        | 42.0  | 26250 | 0.0959          | 0.983 |
| 0.0881        | 43.0  | 26875 | 0.0996          | 0.983 |
| 0.0885        | 44.0  | 27500 | 0.0972          | 0.982 |
| 0.0871        | 45.0  | 28125 | 0.0984          | 0.983 |
| 0.0866        | 46.0  | 28750 | 0.0976          | 0.983 |
| 0.0858        | 47.0  | 29375 | 0.0982          | 0.983 |
| 0.0882        | 48.0  | 30000 | 0.0982          | 0.983 |
| 0.0848        | 49.0  | 30625 | 0.0988          | 0.983 |
| 0.0855        | 50.0  | 31250 | 0.0988          | 0.983 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1