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---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
base_model: openai/whisper-base
model-index:
- name: whisper-base-full-data-language-v2-20ep
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-base-full-data-language-v2-20ep
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1929
## 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: 0.00015
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- training_steps: 63840
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3116 | 1.57 | 5000 | 0.5301 |
| 0.2104 | 3.13 | 10000 | 0.4066 |
| 0.1729 | 4.7 | 15000 | 0.3555 |
| 0.1472 | 6.27 | 20000 | 0.3208 |
| 0.128 | 7.83 | 25000 | 0.2923 |
| 0.1065 | 9.4 | 30000 | 0.2719 |
| 0.0995 | 10.97 | 35000 | 0.2516 |
| 0.0812 | 12.53 | 40000 | 0.2368 |
| 0.066 | 14.1 | 45000 | 0.2230 |
| 0.0574 | 15.67 | 50000 | 0.2119 |
| 0.0463 | 17.23 | 55000 | 0.2028 |
| 0.04 | 18.8 | 60000 | 0.1957 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.1.0a0+gitcc01568
- Datasets 2.13.1
- Tokenizers 0.13.3
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