---
license: apache-2.0
base_model: hughlan1214/SER_wav2vec2-large-xlsr-53_240304_fin-tuned
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: SER_wav2vec2-large-xlsr-53_240304_fin-tuned_2
  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. -->

# SER_wav2vec2-large-xlsr-53_240304_fin-tuned_2

This model is a fine-tuned version of [hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fin-tuned2.0](https://huggingface.co/hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fin-tuned2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0601
- Accuracy: 0.6731
- Precision: 0.6761
- Recall: 0.6794
- F1: 0.6738

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8904        | 1.0   | 1048  | 1.1923          | 0.5773   | 0.6162    | 0.5563 | 0.5494 |
| 1.1394        | 2.0   | 2096  | 1.0143          | 0.6071   | 0.6481    | 0.6189 | 0.6057 |
| 0.9373        | 3.0   | 3144  | 1.0585          | 0.6126   | 0.6296    | 0.6254 | 0.6119 |
| 0.7405        | 4.0   | 4192  | 0.9580          | 0.6514   | 0.6732    | 0.6562 | 0.6576 |
| 1.1638        | 5.0   | 5240  | 0.9940          | 0.6486   | 0.6485    | 0.6627 | 0.6435 |
| 0.6741        | 6.0   | 6288  | 1.0307          | 0.6628   | 0.6710    | 0.6711 | 0.6646 |
| 0.604         | 7.0   | 7336  | 1.0248          | 0.6667   | 0.6678    | 0.6751 | 0.6682 |
| 0.6835        | 8.0   | 8384  | 1.0396          | 0.6722   | 0.6803    | 0.6790 | 0.6743 |
| 0.5421        | 9.0   | 9432  | 1.0493          | 0.6714   | 0.6765    | 0.6785 | 0.6736 |
| 0.5728        | 10.0  | 10480 | 1.0601          | 0.6731   | 0.6761    | 0.6794 | 0.6738 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2