update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- iva_mt_wslot2
+metrics:
+- bleu
+model-index:
+- name: iva_mt_wslot-m2m100_418M-en-de
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: iva_mt_wslot2
+      type: iva_mt_wslot2
+      config: en-de
+      split: validation
+      args: en-de
+    metrics:
+    - name: Bleu
+      type: bleu
+      value: 66.5548
+---
+
+<!-- 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. -->
+
+# iva_mt_wslot-m2m100_418M-en-de
+
+This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0126
+- Bleu: 66.5548
+- Gen Len: 20.6835
+
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
+| 0.0183        | 1.0   | 1884  | 0.0144          | 63.5045 | 20.2994 |
+| 0.0119        | 2.0   | 3768  | 0.0127          | 66.0473 | 20.5423 |
+| 0.0083        | 3.0   | 5652  | 0.0123          | 65.5139 | 20.5409 |
+| 0.0065        | 4.0   | 7536  | 0.0124          | 66.0731 | 20.6114 |
+| 0.0048        | 5.0   | 9420  | 0.0122          | 66.2454 | 20.5906 |
+| 0.0038        | 6.0   | 11304 | 0.0124          | 66.7412 | 20.6263 |
+| 0.0031        | 7.0   | 13188 | 0.0126          | 66.5548 | 20.6835 |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3