---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-fsc
  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. -->

# wav2vec2-base-960h-fsc

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: 0.0218
- Accuracy: 0.9947

## 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: 0.0005
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9959  | 120  | 0.3651          | 0.9380   |
| No log        | 2.0     | 241  | 0.2352          | 0.9404   |
| No log        | 2.9959  | 361  | 0.4245          | 0.8684   |
| No log        | 4.0     | 482  | 0.0721          | 0.9837   |
| No log        | 4.9959  | 602  | 0.0961          | 0.9768   |
| No log        | 6.0     | 723  | 0.0632          | 0.9860   |
| No log        | 6.9959  | 843  | 0.0498          | 0.9905   |
| No log        | 8.0     | 964  | 0.0715          | 0.9834   |
| 0.4012        | 8.9959  | 1084 | 0.0907          | 0.9829   |
| 0.4012        | 10.0    | 1205 | 0.0644          | 0.9860   |
| 0.4012        | 10.9959 | 1325 | 0.0322          | 0.9921   |
| 0.4012        | 12.0    | 1446 | 0.0524          | 0.9881   |
| 0.4012        | 12.9959 | 1566 | 0.0450          | 0.9910   |
| 0.4012        | 14.0    | 1687 | 0.0227          | 0.9942   |
| 0.4012        | 14.9959 | 1807 | 0.0437          | 0.9908   |
| 0.4012        | 16.0    | 1928 | 0.0381          | 0.9924   |
| 0.1096        | 16.9959 | 2048 | 0.0218          | 0.9947   |
| 0.1096        | 18.0    | 2169 | 0.0300          | 0.9934   |
| 0.1096        | 18.9959 | 2289 | 0.0356          | 0.9931   |
| 0.1096        | 20.0    | 2410 | 0.0380          | 0.9937   |
| 0.1096        | 20.9959 | 2530 | 0.0417          | 0.9934   |
| 0.1096        | 22.0    | 2651 | 0.0268          | 0.9947   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1