transformers tensorboard safetensors hubert automatic-speech-recognition generated_from_trainer base_model:facebook/hubert-large-ll60k license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/hubert-large-ll60k
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: HuBERT_Jibbali_lang
  results: []
---

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# HuBERT_Jibbali_lang

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: 0.2017
- Wer: 0.1944
- Cet: 0.1189

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cet    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 10.6563       | 0.99  | 56   | 5.6577          | 1.0    | 0.9812 |
| 3.3895        | 2.0   | 113  | 3.2018          | 1.0    | 0.9812 |
| 3.1588        | 2.99  | 169  | 3.1347          | 1.0    | 0.9812 |
| 3.1308        | 4.0   | 226  | 3.0567          | 1.0    | 0.9812 |
| 2.8933        | 4.99  | 282  | 2.8226          | 1.0    | 0.9353 |
| 2.5444        | 6.0   | 339  | 2.0947          | 1.0    | 0.8588 |
| 0.995         | 6.99  | 395  | 0.5049          | 0.4974 | 0.1654 |
| 0.3567        | 8.0   | 452  | 0.2622          | 0.2485 | 0.1132 |
| 0.2914        | 8.99  | 508  | 0.1980          | 0.2105 | 0.0749 |
| 0.14          | 10.0  | 565  | 0.2154          | 0.2069 | 0.0821 |
| 0.1442        | 10.99 | 621  | 0.1965          | 0.1988 | 0.0969 |
| 0.1401        | 12.0  | 678  | 0.2135          | 0.1937 | 0.0960 |
| 0.1019        | 12.99 | 734  | 0.2185          | 0.1948 | 0.1094 |
| 0.1088        | 14.0  | 791  | 0.1957          | 0.1966 | 0.1121 |
| 0.1314        | 14.99 | 847  | 0.1983          | 0.1933 | 0.1019 |
| 0.0522        | 16.0  | 904  | 0.2026          | 0.1944 | 0.1258 |
| 0.126         | 16.99 | 960  | 0.2033          | 0.1944 | 0.1142 |
| 0.1028        | 18.0  | 1017 | 0.1940          | 0.1974 | 0.1158 |
| 0.0767        | 18.99 | 1073 | 0.1969          | 0.1948 | 0.1149 |
| 0.0468        | 19.82 | 1120 | 0.2017          | 0.1944 | 0.1189 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
