update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+model-index:
+- name: es_fi_all_copy_quy
+  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. -->
+
+# es_fi_all_copy_quy
+
+This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-fi](https://huggingface.co/Helsinki-NLP/opus-mt-es-fi) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4826
+- Bleu: 1.0774
+- Chrf: 27.8374
+- Gen Len: 49.2425
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Chrf    | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:-------:|
+| 0.5479        | 0.03  | 1000  | 0.6737          | 0.3055 | 13.5765 | 61.5895 |
+| 0.4856        | 0.07  | 2000  | 0.6330          | 0.1975 | 16.9698 | 73.9869 |
+| 0.4541        | 0.1   | 3000  | 0.6120          | 0.1727 | 17.4235 | 77.335  |
+| 0.4381        | 0.13  | 4000  | 0.5962          | 0.3781 | 18.0872 | 48.1066 |
+| 0.4236        | 0.17  | 5000  | 0.5880          | 0.3741 | 18.808  | 60.0463 |
+| 0.4165        | 0.2   | 6000  | 0.5721          | 0.4366 | 19.5753 | 54.2746 |
+| 0.3978        | 0.23  | 7000  | 0.5669          | 0.3667 | 20.4865 | 57.9366 |
+| 0.3916        | 0.27  | 8000  | 0.5536          | 0.8014 | 21.485  | 47.503  |
+| 0.3747        | 0.3   | 9000  | 0.5501          | 0.5344 | 21.0513 | 60.3924 |
+| 0.3825        | 0.33  | 10000 | 0.5375          | 0.4356 | 22.2798 | 56.7726 |
+| 0.3716        | 0.36  | 11000 | 0.5390          | 0.5945 | 23.2025 | 53.9366 |
+| 0.3518        | 0.4   | 12000 | 0.5312          | 0.7343 | 23.1143 | 52.326  |
+| 0.3495        | 0.43  | 13000 | 0.5217          | 1.0112 | 24.6907 | 49.3903 |
+| 0.3508        | 0.46  | 14000 | 0.5222          | 0.5915 | 23.556  | 57.2656 |
+| 0.3464        | 0.5   | 15000 | 0.5165          | 0.7044 | 24.2944 | 59.159  |
+| 0.3476        | 0.53  | 16000 | 0.5142          | 1.1    | 25.0408 | 52.1127 |
+| 0.3444        | 0.56  | 17000 | 0.5108          | 0.9361 | 24.8808 | 48.9366 |
+| 0.3404        | 0.6   | 18000 | 0.5056          | 0.9007 | 25.3524 | 51.6962 |
+| 0.3286        | 0.63  | 19000 | 0.5029          | 0.9896 | 24.8249 | 52.7233 |
+| 0.3362        | 0.66  | 20000 | 0.5012          | 0.8774 | 26.6471 | 47.3732 |
+| 0.3386        | 0.7   | 21000 | 0.5028          | 0.8963 | 25.7596 | 54.1861 |
+| 0.3371        | 0.73  | 22000 | 0.5002          | 0.8477 | 24.9775 | 54.2958 |
+| 0.3284        | 0.76  | 23000 | 0.4955          | 0.9197 | 25.5964 | 55.2606 |
+| 0.3239        | 0.8   | 24000 | 0.4943          | 1.1353 | 27.5912 | 48.5714 |
+| 0.3214        | 0.83  | 25000 | 0.4889          | 0.9846 | 26.098  | 51.0221 |
+| 0.3183        | 0.86  | 26000 | 0.4889          | 1.1816 | 28.4223 | 44.1288 |
+| 0.3164        | 0.89  | 27000 | 0.4874          | 1.028  | 27.4202 | 48.2616 |
+| 0.3162        | 0.93  | 28000 | 0.4839          | 1.0008 | 26.1891 | 54.4095 |
+| 0.3167        | 0.96  | 29000 | 0.4837          | 1.1952 | 27.7299 | 47.3159 |
+| 0.3141        | 0.99  | 30000 | 0.4809          | 0.7488 | 27.6076 | 48.9638 |
+| 0.3043        | 1.03  | 31000 | 0.4826          | 1.0774 | 27.8374 | 49.2425 |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu117
+- Datasets 2.11.0
+- Tokenizers 0.13.3