File size: 2,782 Bytes
7e7e661 6bed34b 7e7e661 6bed34b ef5298b 7e7e661 6bed34b 7e7e661 1e124f7 7e7e661 1e124f7 7e7e661 ef5298b 7e7e661 ef5298b 7e7e661 ef5298b 1e124f7 7e7e661 |
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 |
---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Drone test En - Siang Yi
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. -->
# Drone test En - Siang Yi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the drone command test3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6268
- Wer: 8.3333
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use 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_ratio: 0.1
- training_steps: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.86 | 10.0 | 10 | 0.6997 | 25.0 |
| 0.0773 | 20.0 | 20 | 0.1492 | 16.6667 |
| 0.0062 | 30.0 | 30 | 0.5699 | 8.3333 |
| 0.0028 | 40.0 | 40 | 0.5715 | 8.3333 |
| 0.0006 | 50.0 | 50 | 0.5512 | 8.3333 |
| 0.0228 | 60.0 | 60 | 0.6065 | 8.3333 |
| 0.0 | 70.0 | 70 | 0.5899 | 8.3333 |
| 0.0001 | 80.0 | 80 | 0.6822 | 8.3333 |
| 0.0 | 90.0 | 90 | 0.6161 | 8.3333 |
| 0.0 | 100.0 | 100 | 0.6305 | 8.3333 |
| 0.0 | 110.0 | 110 | 0.6301 | 8.3333 |
| 0.0 | 120.0 | 120 | 0.6296 | 8.3333 |
| 0.0 | 130.0 | 130 | 0.6284 | 8.3333 |
| 0.0 | 140.0 | 140 | 0.6283 | 8.3333 |
| 0.0 | 150.0 | 150 | 0.6281 | 8.3333 |
| 0.0 | 160.0 | 160 | 0.6270 | 8.3333 |
| 0.0 | 170.0 | 170 | 0.6280 | 8.3333 |
| 0.0 | 180.0 | 180 | 0.6280 | 8.3333 |
| 0.0 | 190.0 | 190 | 0.6269 | 8.3333 |
| 0.0 | 200.0 | 200 | 0.6268 | 8.3333 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|