Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,87 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
license: apache-2.0
|
| 4 |
+
base_model: openai/whisper-large-v3
|
| 5 |
+
tags:
|
| 6 |
+
- generated_from_trainer
|
| 7 |
+
datasets:
|
| 8 |
+
- fsicoli/cv19-fleurs
|
| 9 |
+
metrics:
|
| 10 |
+
- wer
|
| 11 |
+
model-index:
|
| 12 |
+
- name: whisper-large-v3-pt-cv19-fleurs
|
| 13 |
+
results:
|
| 14 |
+
- task:
|
| 15 |
+
name: Automatic Speech Recognition
|
| 16 |
+
type: automatic-speech-recognition
|
| 17 |
+
dataset:
|
| 18 |
+
name: fsicoli/cv19-fleurs default
|
| 19 |
+
type: fsicoli/cv19-fleurs
|
| 20 |
+
args: default
|
| 21 |
+
metrics:
|
| 22 |
+
- name: Wer
|
| 23 |
+
type: wer
|
| 24 |
+
value: 0.0756
|
| 25 |
+
---
|
| 26 |
+
|
| 27 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 28 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 29 |
+
|
| 30 |
+
# whisper-large-v3-pt-cv19-fleurs-ct2
|
| 31 |
+
|
| 32 |
+
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the fsicoli/cv19-fleurs default dataset converted to CT2.
|
| 33 |
+
It achieves the following results on the evaluation set:
|
| 34 |
+
- Loss: 0.1823
|
| 35 |
+
- Wer: 0.0756
|
| 36 |
+
|
| 37 |
+
## Model description
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Intended uses & limitations
|
| 42 |
+
|
| 43 |
+
More information needed
|
| 44 |
+
|
| 45 |
+
## Training and evaluation data
|
| 46 |
+
|
| 47 |
+
More information needed
|
| 48 |
+
|
| 49 |
+
## Training procedure
|
| 50 |
+
|
| 51 |
+
### Training hyperparameters
|
| 52 |
+
|
| 53 |
+
The following hyperparameters were used during training:
|
| 54 |
+
- learning_rate: 6.25e-06
|
| 55 |
+
- train_batch_size: 8
|
| 56 |
+
- eval_batch_size: 8
|
| 57 |
+
- seed: 42
|
| 58 |
+
- gradient_accumulation_steps: 2
|
| 59 |
+
- total_train_batch_size: 16
|
| 60 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 61 |
+
- lr_scheduler_type: linear
|
| 62 |
+
- lr_scheduler_warmup_steps: 10000
|
| 63 |
+
- training_steps: 50000
|
| 64 |
+
- mixed_precision_training: Native AMP
|
| 65 |
+
|
| 66 |
+
### Training results
|
| 67 |
+
|
| 68 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
| 69 |
+
|:-------------:|:-------:|:-----:|:---------------:|:------:|
|
| 70 |
+
| 0.0559 | 2.2883 | 5000 | 0.1096 | 0.0730 |
|
| 71 |
+
| 0.0581 | 4.5767 | 10000 | 0.1326 | 0.0829 |
|
| 72 |
+
| 0.0225 | 6.8650 | 15000 | 0.1570 | 0.0849 |
|
| 73 |
+
| 0.0088 | 9.1533 | 20000 | 0.1704 | 0.0840 |
|
| 74 |
+
| 0.0065 | 11.4416 | 25000 | 0.1823 | 0.0849 |
|
| 75 |
+
| 0.006 | 13.7300 | 30000 | 0.1808 | 0.0809 |
|
| 76 |
+
| 0.0055 | 16.0183 | 35000 | 0.1811 | 0.0790 |
|
| 77 |
+
| 0.0031 | 18.3066 | 40000 | 0.1907 | 0.0784 |
|
| 78 |
+
| 0.0011 | 20.5950 | 45000 | 0.1852 | 0.0771 |
|
| 79 |
+
| 0.0003 | 22.8833 | 50000 | 0.1848 | 0.0756 |
|
| 80 |
+
|
| 81 |
+
|
| 82 |
+
### Framework versions
|
| 83 |
+
|
| 84 |
+
- Transformers 4.45.0.dev0
|
| 85 |
+
- Pytorch 2.4.1
|
| 86 |
+
- Datasets 2.21.0
|
| 87 |
+
- Tokenizers 0.19.1
|