Model save

README.md

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+---
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: mms-MGB3
+  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. -->
+
+# mms-MGB3
+
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9382
+- Wer: 0.6591
+
+## 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: 14
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 9.7535        | 0.13  | 250  | 8.6735          | 1.0023 |
+| 3.2385        | 0.27  | 500  | 3.3341          | 1.0003 |
+| 2.3512        | 0.4   | 750  | 2.0937          | 0.9027 |
+| 1.4967        | 0.53  | 1000 | 1.3694          | 0.7637 |
+| 1.3214        | 0.67  | 1250 | 1.2237          | 0.7347 |
+| 1.2072        | 0.8   | 1500 | 1.1672          | 0.7176 |
+| 1.1913        | 0.93  | 1750 | 1.1334          | 0.7108 |
+| 1.1127        | 1.07  | 2000 | 1.1102          | 0.7044 |
+| 1.1454        | 1.2   | 2250 | 1.0919          | 0.6996 |
+| 1.1128        | 1.33  | 2500 | 1.0763          | 0.6955 |
+| 1.086         | 1.47  | 2750 | 1.0629          | 0.6916 |
+| 1.1285        | 1.6   | 3000 | 1.0503          | 0.6888 |
+| 1.081         | 1.73  | 3250 | 1.0406          | 0.6886 |
+| 1.0449        | 1.86  | 3500 | 1.0320          | 0.6857 |
+| 1.0625        | 2.0   | 3750 | 1.0231          | 0.6849 |
+| 1.0892        | 2.13  | 4000 | 1.0157          | 0.6824 |
+| 1.0566        | 2.26  | 4250 | 1.0097          | 0.6795 |
+| 1.0972        | 2.4   | 4500 | 1.0036          | 0.6747 |
+| 1.0617        | 2.53  | 4750 | 0.9957          | 0.6744 |
+| 1.0441        | 2.66  | 5000 | 0.9881          | 0.6756 |
+| 1.0589        | 2.8   | 5250 | 0.9807          | 0.6718 |
+| 1.0005        | 2.93  | 5500 | 0.9758          | 0.6713 |
+| 1.0447        | 3.06  | 5750 | 0.9701          | 0.6694 |
+| 0.9722        | 3.2   | 6000 | 0.9667          | 0.6664 |
+| 0.9873        | 3.33  | 6250 | 0.9595          | 0.6675 |
+| 0.9857        | 3.46  | 6500 | 0.9551          | 0.6633 |
+| 0.9625        | 3.6   | 6750 | 0.9519          | 0.6633 |
+| 0.9748        | 3.73  | 7000 | 0.9464          | 0.6607 |
+| 0.9626        | 3.86  | 7250 | 0.9427          | 0.6617 |
+| 1.0242        | 4.0   | 7500 | 0.9382          | 0.6591 |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1
+- Datasets 2.19.1
+- Tokenizers 0.13.3

adapter.ara.safetensors

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