---
base_model: facebook/wav2vec2-base-960h
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-960h-EMOPIA-10sec
  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-EMOPIA-10sec

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: 2.5866
- Accuracy: 0.6338

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2014        | 1.0   | 807   | 1.1830          | 0.3662   |
| 1.0915        | 2.0   | 1614  | 1.5120          | 0.3239   |
| 1.1433        | 3.0   | 2421  | 1.5699          | 0.4085   |
| 1.2819        | 4.0   | 3228  | 1.7372          | 0.4789   |
| 1.2718        | 5.0   | 4035  | 2.2169          | 0.4648   |
| 1.4535        | 6.0   | 4842  | 1.7296          | 0.5775   |
| 1.3433        | 7.0   | 5649  | 2.2684          | 0.5493   |
| 1.4086        | 8.0   | 6456  | 1.8599          | 0.6479   |
| 1.3923        | 9.0   | 7263  | 1.9420          | 0.6197   |
| 1.3353        | 10.0  | 8070  | 2.2150          | 0.5775   |
| 1.367         | 11.0  | 8877  | 1.9826          | 0.6338   |
| 1.1848        | 12.0  | 9684  | 1.9545          | 0.6479   |
| 1.1355        | 13.0  | 10491 | 1.9864          | 0.6620   |
| 1.1549        | 14.0  | 11298 | 1.9428          | 0.6338   |
| 1.0505        | 15.0  | 12105 | 1.9101          | 0.6901   |
| 1.0442        | 16.0  | 12912 | 2.1706          | 0.6479   |
| 0.9922        | 17.0  | 13719 | 2.4620          | 0.6197   |
| 0.8698        | 18.0  | 14526 | 2.1429          | 0.6620   |
| 0.8202        | 19.0  | 15333 | 2.3725          | 0.6197   |
| 0.8612        | 20.0  | 16140 | 2.1631          | 0.6620   |
| 0.8197        | 21.0  | 16947 | 2.3932          | 0.6338   |
| 0.7858        | 22.0  | 17754 | 2.2532          | 0.6479   |
| 0.7717        | 23.0  | 18561 | 2.8132          | 0.5634   |
| 0.6282        | 24.0  | 19368 | 2.5493          | 0.6197   |
| 0.7394        | 25.0  | 20175 | 2.3195          | 0.6620   |
| 0.5895        | 26.0  | 20982 | 2.4331          | 0.6620   |
| 0.5854        | 27.0  | 21789 | 2.4281          | 0.6761   |
| 0.6911        | 28.0  | 22596 | 2.4993          | 0.6620   |
| 0.5502        | 29.0  | 23403 | 2.6458          | 0.6338   |
| 0.584         | 30.0  | 24210 | 2.5866          | 0.6338   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.0