File size: 1,850 Bytes
0b9e06e 4d7a6b0 0b9e06e 4d7a6b0 b45a6ed 0b9e06e b45a6ed 0b9e06e 4d7a6b0 b45a6ed 0b9e06e 26f015e 0b9e06e 26f015e 0b9e06e 4d7a6b0 b45a6ed 0b9e06e 5620633 b45a6ed 5620633 0b9e06e 4d7a6b0 5620633 0b9e06e |
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 |
---
library_name: transformers
license: mit
base_model: distil-whisper/distil-small.en
tags:
- generated_from_trainer
datasets:
- generator
metrics:
- wer
model-index:
- name: distil_whisper_en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: generator
type: generator
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 0.8298755186721992
---
<!-- 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. -->
# distil_whisper_en
This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.8299
## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0 | 19.031 | 500 | 0.0000 | 0.8299 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
|