File size: 2,046 Bytes
6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 6ba3e0d a4eb1c9 |
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 |
---
license: mit
base_model: bofenghuang/whisper-large-v3-french-distil-dec16
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 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. -->
# whisper
This model is a fine-tuned version of [bofenghuang/whisper-large-v3-french-distil-dec16](https://huggingface.co/bofenghuang/whisper-large-v3-french-distil-dec16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1122
- Wer: 5.3589
## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 200
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4042 | 0.38 | 20 | 0.2881 | 4.5501 |
| 0.3463 | 0.77 | 40 | 0.2060 | 4.3478 |
| 0.125 | 1.15 | 60 | 0.1498 | 4.7523 |
| 0.0606 | 1.54 | 80 | 0.1154 | 4.3478 |
| 0.0884 | 1.92 | 100 | 0.1026 | 4.8534 |
| 0.0189 | 2.31 | 120 | 0.0995 | 4.8534 |
| 0.0235 | 2.69 | 140 | 0.1085 | 4.6512 |
| 0.0126 | 3.08 | 160 | 0.1100 | 4.6512 |
| 0.0096 | 3.46 | 180 | 0.1114 | 5.2578 |
| 0.0214 | 3.85 | 200 | 0.1122 | 5.3589 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
|