---
datasets:
- fleurs
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: NewSpeechModel-V3.0
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: fleurs
      type: fleurs
      config: so_so
      split: validation
      args: so_so
    metrics:
    - type: wer
      value: 1.0
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# NewSpeechModel-V3.0

This model was trained from scratch on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8201
- Wer: 1.0

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| 18.0665       | 0.0960 | 10   | 11.8649         | 1.0 |
| 9.3649        | 0.1919 | 20   | 4.3831          | 1.0 |
| 3.9649        | 0.2879 | 30   | 8.1376          | 1.0 |
| 4.9612        | 0.3839 | 40   | 2.9464          | 1.0 |
| 2.8949        | 0.4798 | 50   | 2.8598          | 1.0 |
| 2.9052        | 0.5758 | 60   | 2.8362          | 1.0 |
| 2.8514        | 0.6718 | 70   | 2.8395          | 1.0 |
| 3.1088        | 0.7678 | 80   | 2.8443          | 1.0 |
| 2.8454        | 0.8637 | 90   | 2.8211          | 1.0 |
| 2.8211        | 0.9597 | 100  | 2.8201          | 1.0 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1