Create README.md

README.md

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+---
+language:
+- gl
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_8_0
+- generated_from_trainer
+- gl
+- robust-speech-event
+- model_for_talk
+datasets:
+- mozilla-foundation/common_voice_8_0
+
+model-index:
+- name: Akashpb13/Galician_xlsr
+  results:
+  - task: 
+      name: Automatic Speech Recognition 
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 8
+      type: mozilla-foundation/common_voice_8_0
+      args: kmr
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.11308483789555426
+       - name: Test CER
+         type: cer
+         value: 0.023982371794871796
+  - task: 
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: gl
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.11308483789555426
+       - name: Test CER
+         type: cer
+         value: 0.023982371794871796
+---
+
+# Akashpb13/xlsr_hungarian_new
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
+It achieves the following results on the evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, and dev datasets):
+- Loss: 0.137096
+- Wer: 0.196230
+## Model description
+"facebook/wav2vec2-xls-r-300m" was finetuned.
+
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+Training data - 
+Common voice Galician train.tsv, dev.tsv, invalidated.tsv, reported.tsv, other.tsv and validated.tsv
+Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0
+
+## Training procedure
+For creating the training dataset, all possible datasets were appended and 90-10 split was used. 
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+
+- learning_rate: 0.000096
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 13
+- gradient_accumulation_steps: 2
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+
+
+### Training results
+
+| Step | Training Loss | Validation Loss | Wer      |
+|------|---------------|-----------------|----------|
+| 500  | 5.004400      | 2.960605        | 1.000000 |
+| 1000 | 1.653100      | 0.248843        | 0.354571 |
+| 1500 | 0.259100      | 0.149203        | 0.251272 |
+| 2000 | 0.155200      | 0.142355        | 0.227521 |
+| 2500 | 0.118900      | 0.134033        | 0.217154 |
+| 3000 | 0.100200      | 0.134676        | 0.216588 |
+| 3500 | 0.085800      | 0.138649        | 0.219416 |
+| 4000 | 0.075700      | 0.138660        | 0.212441 |
+| 4500 | 0.066200      | 0.142651        | 0.208671 |
+| 5000 | 0.060300      | 0.136673        | 0.204713 |
+| 5500 | 0.054600      | 0.132755        | 0.202828 |
+| 6000 | 0.048100      | 0.136589        | 0.198115 |
+| 6500 | 0.044800      | 0.140990        | 0.199246 |
+| 7000 | 0.039700      | 0.136947        | 0.196984 |
+| 7500 | 0.040200      | 0.140098        | 0.196418 |
+| 8000 | 0.037800      | 0.137096        | 0.196230 |
+
+
+### Framework versions
+- Transformers 4.16.0.dev0
+- Pytorch 1.10.0+cu102
+- Datasets 1.17.1.dev0
+- Tokenizers 0.10.3
+
+#### Evaluation Commands
+
+1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
+
+```bash
+python eval.py --model_id Akashpb13/Galician_xlsr --dataset mozilla-foundation/common_voice_8_0 --config gl --split test
+```
+