---
license: apache-2.0
base_model: facebook/hubert-xlarge-ll60k
tags:
- generated_from_trainer
model-index:
- name: hubert_xlarge_emodb
  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_xlarge_emodb

This model is a fine-tuned version of [facebook/hubert-xlarge-ll60k](https://huggingface.co/facebook/hubert-xlarge-ll60k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8345
- Uar: 0.8889
- Acc: 0.9118

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Uar    | Acc    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 0.2   | 5    | 1.3815          | 0.25   | 0.1985 |
| No log        | 0.39  | 10   | 1.3436          | 0.5285 | 0.5956 |
| No log        | 0.59  | 15   | 1.3028          | 0.5741 | 0.6618 |
| No log        | 0.78  | 20   | 1.2412          | 0.6019 | 0.6838 |
| No log        | 0.98  | 25   | 1.1652          | 0.75   | 0.8015 |
| 1.2216        | 1.18  | 30   | 1.0883          | 0.7315 | 0.7868 |
| 1.2216        | 1.37  | 35   | 1.0309          | 0.75   | 0.8015 |
| 1.2216        | 1.57  | 40   | 1.0217          | 0.8335 | 0.8603 |
| 1.2216        | 1.76  | 45   | 1.0084          | 0.8714 | 0.8529 |
| 1.2216        | 1.96  | 50   | 0.9415          | 0.7778 | 0.8235 |
| 0.5781        | 2.16  | 55   | 0.9293          | 0.7870 | 0.8309 |
| 0.5781        | 2.35  | 60   | 0.8470          | 0.9448 | 0.9412 |
| 0.5781        | 2.55  | 65   | 0.8673          | 0.8333 | 0.8676 |
| 0.5781        | 2.75  | 70   | 0.8454          | 0.9074 | 0.9265 |
| 0.5781        | 2.94  | 75   | 0.8139          | 0.9167 | 0.9338 |
| 0.2652        | 3.14  | 80   | 0.8254          | 0.8981 | 0.9191 |
| 0.2652        | 3.33  | 85   | 0.8233          | 0.9074 | 0.9265 |
| 0.2652        | 3.53  | 90   | 0.7989          | 0.9259 | 0.9412 |
| 0.2652        | 3.73  | 95   | 0.7939          | 0.9584 | 0.9632 |
| 0.2652        | 3.92  | 100  | 0.8093          | 0.9167 | 0.9338 |
| 0.1537        | 4.12  | 105  | 0.8138          | 0.9167 | 0.9338 |
| 0.1537        | 4.31  | 110  | 0.7898          | 0.9539 | 0.9559 |
| 0.1537        | 4.51  | 115  | 0.8138          | 0.9074 | 0.9265 |
| 0.1537        | 4.71  | 120  | 0.8463          | 0.8704 | 0.8971 |
| 0.1537        | 4.9   | 125  | 0.8643          | 0.8519 | 0.8824 |
| 0.1615        | 5.1   | 130  | 0.8137          | 0.9074 | 0.9265 |
| 0.1615        | 5.29  | 135  | 0.7750          | 0.9724 | 0.9706 |
| 0.1615        | 5.49  | 140  | 0.7745          | 0.9724 | 0.9706 |
| 0.1615        | 5.69  | 145  | 0.8123          | 0.9074 | 0.9265 |
| 0.1615        | 5.88  | 150  | 0.8693          | 0.8426 | 0.875  |
| 0.0762        | 6.08  | 155  | 0.9067          | 0.7870 | 0.8309 |
| 0.0762        | 6.27  | 160  | 0.9123          | 0.7870 | 0.8309 |
| 0.0762        | 6.47  | 165  | 0.8664          | 0.8426 | 0.875  |
| 0.0762        | 6.67  | 170  | 0.8167          | 0.9074 | 0.9265 |
| 0.0762        | 6.86  | 175  | 0.8104          | 0.9259 | 0.9412 |
| 0.1321        | 7.06  | 180  | 0.8222          | 0.8981 | 0.9191 |
| 0.1321        | 7.25  | 185  | 0.8339          | 0.8889 | 0.9118 |
| 0.1321        | 7.45  | 190  | 0.8468          | 0.8704 | 0.8971 |
| 0.1321        | 7.65  | 195  | 0.8453          | 0.8704 | 0.8971 |
| 0.1321        | 7.84  | 200  | 0.8453          | 0.8704 | 0.8971 |
| 0.027         | 8.04  | 205  | 0.8346          | 0.8889 | 0.9118 |
| 0.027         | 8.24  | 210  | 0.8292          | 0.8889 | 0.9118 |
| 0.027         | 8.43  | 215  | 0.8276          | 0.8889 | 0.9118 |
| 0.027         | 8.63  | 220  | 0.8353          | 0.8889 | 0.9118 |
| 0.027         | 8.82  | 225  | 0.8376          | 0.8889 | 0.9118 |
| 0.0499        | 9.02  | 230  | 0.8327          | 0.8889 | 0.9118 |
| 0.0499        | 9.22  | 235  | 0.8317          | 0.8889 | 0.9118 |
| 0.0499        | 9.41  | 240  | 0.8330          | 0.8889 | 0.9118 |
| 0.0499        | 9.61  | 245  | 0.8343          | 0.8889 | 0.9118 |
| 0.0499        | 9.8   | 250  | 0.8345          | 0.8889 | 0.9118 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3