update model card README.md

README.md

@@ -1,57 +1,12 @@
 ---
-language: 
-- ar
-
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- robust-speech-event
+- generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_7_0
-metrics:
-- wer
-- cer
+- common_voice
 model-index:
-- name: wav2vec2-xls-r-300m-arabic
-  results:
-  - task: 
-      type: automatic-speech-recognition  # Required. Example: automatic-speech-recognition
-      name: Speech Recognition  # Optional. Example: Speech Recognition
-    dataset:
-      type: mozilla-foundation/common_voice_7_0  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: Common Voice ar # Required. Example: Common Voice zh-CN
-      args: ar        # Optional. Example: zh-CN
-    metrics:
-      - type: wer    # Required. Example: wer
-        value: 31.05  # Required. Example: 20.90
-        name: Test WER    # Optional. Example: Test WER
-        args: 
-        - learning_rate: 0.0003
-        - train_batch_size: 64
-        - eval_batch_size: 8
-        - seed: 42
-        - gradient_accumulation_steps: 2
-        - total_train_batch_size: 128
-        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-        - lr_scheduler_type: linear
-        - lr_scheduler_warmup_steps: 1000
-        - num_epochs: 10
-        - mixed_precision_training: Native AMP         # Optional. Example for BLEU: max_order
-      - type: cer    # Required. Example: wer
-        value: 8.78  # Required. Example: 20.90
-        name: Test CER    # Optional. Example: Test WER
-        args: 
-        - learning_rate: 0.0003
-        - train_batch_size: 64
-        - eval_batch_size: 8
-        - seed: 42
-        - gradient_accumulation_steps: 2
-        - total_train_batch_size: 128
-        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-        - lr_scheduler_type: linear
-        - lr_scheduler_warmup_steps: 1000
-        - num_epochs: 10
-        - mixed_precision_training: Native AMP         # Optional. Example for BLEU: max_order
+- name: wav2vec2-large-xlsr-300-arabic
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -61,9 +16,21 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3384
-- Wer: 0.3105
-- Cer: 0.0879
+- Loss: 0.4514
+- Wer: 0.4256
+- Cer: 0.1528
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
 
 ## Training procedure
 
@@ -86,16 +53,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
-| 0.7383        | 1.8   | 500  | 0.4292          | 0.4065 | 0.1189 |
-| 0.664         | 3.6   | 1000 | 0.4245          | 0.3978 | 0.1175 |
-| 0.6064        | 5.4   | 1500 | 0.3854          | 0.3625 | 0.1048 |
-| 0.5221        | 7.19  | 2000 | 0.3819          | 0.3400 | 0.0976 |
-| 0.4591        | 8.99  | 2500 | 0.3384          | 0.3105 | 0.0879 |
+| 5.4375        | 1.8   | 500  | 3.3330          | 1.0    | 1.0    |
+| 2.2187        | 3.6   | 1000 | 0.7790          | 0.6501 | 0.2338 |
+| 0.9471        | 5.4   | 1500 | 0.5353          | 0.5015 | 0.1822 |
+| 0.7416        | 7.19  | 2000 | 0.4889          | 0.4490 | 0.1640 |
+| 0.6358        | 8.99  | 2500 | 0.4514          | 0.4256 | 0.1528 |
 
 
 ### Framework versions
 
-- Transformers 4.16.0.dev0
-- Pytorch 1.10.1+cu102
-- Datasets 1.17.1.dev0
+- Transformers 4.17.0.dev0
+- Pytorch 1.10.2+cu102
+- Datasets 1.18.2.dev0
 - Tokenizers 0.11.0