update model card README.md

README.md

@@ -1,17 +1,63 @@
 ---
-dataset: 
-- google/fleurs
-dataset_tags: 
-- google/fleurs
-language: ta
-model_name: 
-- Whisper Small Tamil
+language:
+- ta_in
+license: apache-2.0
 tags:
 - whisper-event
-- hf-asr-leaderboard
-tasks: 
-- automatic-speech-recognition
-metrics:
-- wer
-license: cc
+- generated_from_trainer
+datasets:
+- google/fleurs
+model-index:
+- name: whisper-small-tamil
+  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-small-tamil
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 4.3680
+- eval_wer: 14.7514
+- eval_runtime: 957.052
+- eval_samples_per_second: 0.608
+- eval_steps_per_second: 0.076
+- step: 0
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1
+- Tokenizers 0.13.2