metadata
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
name: Wer
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