File size: 2,661 Bytes
533fc81 |
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 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
---
library_name: transformers
language:
- ro
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Tiny Ro (local) - Augustin Jianu
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: ro
split: test
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 37.48352861569144
---
<!-- 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. -->
# Whisper Tiny Ro (local) - Augustin Jianu
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5978
- Wer: 37.4835
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.4417 | 1.7730 | 1000 | 0.5327 | 43.8513 |
| 0.1813 | 3.5461 | 2000 | 0.4666 | 38.8689 |
| 0.0751 | 5.3191 | 3000 | 0.4645 | 36.5006 |
| 0.0326 | 7.0922 | 4000 | 0.4803 | 36.4614 |
| 0.0234 | 8.8652 | 5000 | 0.5087 | 36.5148 |
| 0.0082 | 10.6383 | 6000 | 0.5424 | 36.6252 |
| 0.0042 | 12.4113 | 7000 | 0.5650 | 37.6509 |
| 0.0029 | 14.1844 | 8000 | 0.5809 | 36.8710 |
| 0.0025 | 15.9574 | 9000 | 0.5922 | 38.1495 |
| 0.0021 | 17.7305 | 10000 | 0.5978 | 37.4835 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|