---
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-full
  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-full

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: 1.2928
- Accuracy: 0.8488

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2057        | 1.0   | 2248  | 1.4522          | 0.4502   |
| 1.3873        | 2.0   | 4496  | 1.4503          | 0.6423   |
| 1.4246        | 3.0   | 6744  | 1.6165          | 0.6673   |
| 1.3335        | 4.0   | 8992  | 1.4786          | 0.7206   |
| 1.251         | 5.0   | 11240 | 1.6414          | 0.6886   |
| 1.1859        | 6.0   | 13488 | 1.3300          | 0.7544   |
| 1.1132        | 7.0   | 15736 | 1.3665          | 0.7509   |
| 1.0189        | 8.0   | 17984 | 1.6665          | 0.7153   |
| 0.9807        | 9.0   | 20232 | 1.1175          | 0.7794   |
| 0.8786        | 10.0  | 22480 | 1.1786          | 0.7883   |
| 0.8677        | 11.0  | 24728 | 1.1295          | 0.7811   |
| 0.7554        | 12.0  | 26976 | 1.1185          | 0.8185   |
| 0.7196        | 13.0  | 29224 | 1.4067          | 0.7847   |
| 0.692         | 14.0  | 31472 | 1.1175          | 0.8203   |
| 0.6276        | 15.0  | 33720 | 1.4490          | 0.7883   |
| 0.6083        | 16.0  | 35968 | 1.0983          | 0.8345   |
| 0.5204        | 17.0  | 38216 | 1.1814          | 0.8256   |
| 0.5197        | 18.0  | 40464 | 1.2945          | 0.8167   |
| 0.488         | 19.0  | 42712 | 1.4494          | 0.8025   |
| 0.4714        | 20.0  | 44960 | 1.3499          | 0.8114   |
| 0.3641        | 21.0  | 47208 | 1.2525          | 0.8381   |
| 0.3877        | 22.0  | 49456 | 1.2610          | 0.8381   |
| 0.3253        | 23.0  | 51704 | 1.3913          | 0.8274   |
| 0.2978        | 24.0  | 53952 | 1.2990          | 0.8416   |
| 0.3238        | 25.0  | 56200 | 1.4328          | 0.8274   |
| 0.2669        | 26.0  | 58448 | 1.3079          | 0.8327   |
| 0.2521        | 27.0  | 60696 | 1.3250          | 0.8399   |
| 0.2632        | 28.0  | 62944 | 1.3357          | 0.8416   |
| 0.2655        | 29.0  | 65192 | 1.2957          | 0.8434   |
| 0.2379        | 30.0  | 67440 | 1.2928          | 0.8488   |


### Framework versions

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