metadata

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: []

w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1

This model is a fine-tuned version of 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