---
license: apache-2.0
base_model: facebook/hubert-large-ll60k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-large-ll60k-finetuned-ravdess-v4
  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. -->

# hubert-large-ll60k-finetuned-ravdess-v4

This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0831
- Accuracy: 0.625

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0806        | 1.0   | 18   | 2.0768          | 0.1493   |
| 2.0707        | 2.0   | 36   | 2.0653          | 0.1771   |
| 2.0551        | 3.0   | 54   | 2.0475          | 0.1771   |
| 2.0223        | 4.0   | 72   | 2.0066          | 0.2153   |
| 1.8973        | 5.0   | 90   | 1.8130          | 0.2882   |
| 1.8547        | 6.0   | 108  | 1.8352          | 0.2847   |
| 1.7718        | 7.0   | 126  | 1.8253          | 0.2847   |
| 1.722         | 8.0   | 144  | 1.7302          | 0.2986   |
| 1.7004        | 9.0   | 162  | 1.7978          | 0.3160   |
| 1.6574        | 10.0  | 180  | 1.6873          | 0.3507   |
| 1.6387        | 11.0  | 198  | 1.7008          | 0.3576   |
| 1.5605        | 12.0  | 216  | 1.5569          | 0.4340   |
| 1.488         | 13.0  | 234  | 1.4882          | 0.4444   |
| 1.4243        | 14.0  | 252  | 1.4232          | 0.4653   |
| 1.3775        | 15.0  | 270  | 1.4478          | 0.4410   |
| 1.3716        | 16.0  | 288  | 1.3412          | 0.5035   |
| 1.2768        | 17.0  | 306  | 1.3833          | 0.4688   |
| 1.2841        | 18.0  | 324  | 1.3048          | 0.5069   |
| 1.2193        | 19.0  | 342  | 1.2395          | 0.5521   |
| 1.202         | 20.0  | 360  | 1.2025          | 0.5660   |
| 1.169         | 21.0  | 378  | 1.2574          | 0.5312   |
| 1.164         | 22.0  | 396  | 1.1877          | 0.5521   |
| 1.0749        | 23.0  | 414  | 1.1508          | 0.5764   |
| 1.0779        | 24.0  | 432  | 1.1783          | 0.5556   |
| 1.0732        | 25.0  | 450  | 1.1438          | 0.5625   |
| 1.016         | 26.0  | 468  | 1.1971          | 0.5590   |
| 1.022         | 27.0  | 486  | 1.1014          | 0.6042   |
| 1.0345        | 28.0  | 504  | 1.0626          | 0.6215   |
| 1.0081        | 29.0  | 522  | 1.0928          | 0.6181   |
| 1.0036        | 30.0  | 540  | 1.0831          | 0.625    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3