File size: 2,305 Bytes
5aad61d |
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 |
---
license: apache-2.0
base_model: davidilag/whisper-tiny-no-is-5k-steps
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: whisper-tiny-no-is-fo-5k-steps
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ravnursson_asr
type: ravnursson_asr
config: ravnursson_asr
split: test
args: ravnursson_asr
metrics:
- name: Wer
type: wer
value: 37.08475941211999
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/setur/huggingface/runs/60oes3gk)
# whisper-tiny-no-is-fo-5k-steps
This model is a fine-tuned version of [davidilag/whisper-tiny-no-is-5k-steps](https://huggingface.co/davidilag/whisper-tiny-no-is-5k-steps) on the ravnursson_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4949
- Wer: 37.0848
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.8742 | 0.2320 | 1000 | 0.8323 | 52.9696 |
| 0.631 | 0.4640 | 2000 | 0.6234 | 43.8242 |
| 0.5583 | 0.6961 | 3000 | 0.5439 | 39.9487 |
| 0.557 | 0.9281 | 4000 | 0.5060 | 37.6434 |
| 0.46 | 1.1601 | 5000 | 0.4949 | 37.0848 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|