File size: 1,732 Bytes
3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d 3f65e6a 019c53d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | ---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Quechua_Project_Whisper
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. -->
# Quechua_Project_Whisper
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0580
- Wer: 1442.0775
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|
| 5.2233 | 0.3388 | 1000 | 5.3550 | 1952.6512 |
| 4.3345 | 0.6775 | 2000 | 4.7009 | 1775.3798 |
| 3.849 | 1.0163 | 3000 | 4.2552 | 1539.1008 |
| 3.2258 | 1.3550 | 4000 | 4.0580 | 1442.0775 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|