update model card README.md

README.md

@@ -0,0 +1,81 @@
+---
+language:
+- fr
+license: apache-2.0
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- defined.ai
+metrics:
+- wer
+model-index:
+- name: Whisper Small - QC French Sample Retail Dataset
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: AFI_fr
+      type: defined.ai
+      config: es
+      split: test
+      args: es
+    metrics:
+    - name: Wer
+      type: wer
+      value: 8.703419780676679
+---
+
+<!-- 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 - QC French Sample Retail Dataset
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AFI_fr dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2166
+- Wer: 8.7034
+
+## 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: 32
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.1996        | 1.0   | 1000 | 0.2166          | 8.7034 |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.1+cu117
+- Datasets 2.7.1.dev0
+- Tokenizers 0.13.2