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w2v-bert-2.0-tamil-gpu-custom_preprocessed_v1

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 ---
-library_name: transformers
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-# Model Card for Model ID
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 ---
+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

runs/Apr30_17-13-37_GPU/events.out.tfevents.1714477927.GPU.9587.0 CHANGED Viewed

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