Model save

README.md

@@ -1,42 +1,40 @@
 ---
 library_name: transformers
-language:
-- fa
 license: apache-2.0
 base_model: openai/whisper-tiny
 tags:
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_17_0
+- common_voice_17_0
 metrics:
 - wer
 model-index:
-- name: 'Whisper tiny Fa '
+- name: whisper-tiny-fa
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: Common Voice 17.0
-      type: mozilla-foundation/common_voice_17_0
+      name: common_voice_17_0
+      type: common_voice_17_0
       config: fa
       split: None
-      args: 'config: fa, split: test'
+      args: fa
     metrics:
     - name: Wer
       type: wer
-      value: 51.8555393407073
+      value: 117.69616026711185
 ---
 
 <!-- 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 tiny Fa 
+# whisper-tiny-fa
 
-This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset.
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_17_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5542
-- Wer: 51.8555
+- Loss: 2.2460
+- Wer: 117.6962
 
 ## Model description
 
@@ -56,23 +54,19 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 32
+- train_batch_size: 5
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 1000
-- training_steps: 5000
+- training_steps: 1000
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.5002        | 0.8110 | 1000 | 0.7493          | 67.9014 |
-| 0.3239        | 1.6221 | 2000 | 0.6166          | 58.6680 |
-| 0.2198        | 2.4331 | 3000 | 0.5782          | 54.3310 |
-| 0.1695        | 3.2441 | 4000 | 0.5619          | 52.7925 |
-| 0.1309        | 4.0552 | 5000 | 0.5542          | 51.8555 |
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0147        | 25.0  | 1000 | 2.2460          | 117.6962 |
 
 
 ### Framework versions