File size: 1,448 Bytes
0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 0ee5fff 5d6bf85 |
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 |
---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
model-index:
- name: w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1
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. -->
# w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: inf
- eval_wer: 0.4790
- eval_runtime: 231.2694
- eval_samples_per_second: 18.922
- eval_steps_per_second: 2.365
- epoch: 3.17
- step: 3900
## 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: 4.83567e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|