update model card README.md

README.md

@@ -0,0 +1,92 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- amazon_reviews_multi
+metrics:
+- rouge
+model-index:
+- name: mt5-small-finetuned-amazon-en-es
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: amazon_reviews_multi
+      type: amazon_reviews_multi
+      config: en
+      split: validation
+      args: en
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 19.7803
+---
+
+<!-- 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. -->
+
+# mt5-small-finetuned-amazon-en-es
+
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the amazon_reviews_multi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.3776
+- Rouge1: 19.7803
+- Rouge2: 11.1015
+- Rougel: 19.2549
+- Rougelsum: 19.0799
+
+## 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: 5.6e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 16
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
+| 2.7004        | 1.0   | 514  | 3.2936          | 17.2056 | 9.3595  | 17.2163 | 16.8991   |
+| 2.6472        | 2.0   | 1028 | 3.2995          | 17.4081 | 9.9623  | 17.3287 | 16.9701   |
+| 2.6173        | 3.0   | 1542 | 3.3039          | 17.9581 | 9.5537  | 17.7729 | 17.6022   |
+| 2.5812        | 4.0   | 2056 | 3.3057          | 17.438  | 8.8331  | 17.1341 | 17.0436   |
+| 2.5446        | 5.0   | 2570 | 3.3316          | 18.6351 | 10.4851 | 18.5086 | 18.2872   |
+| 2.5133        | 6.0   | 3084 | 3.3255          | 19.1331 | 10.3396 | 18.8557 | 18.6551   |
+| 2.4885        | 7.0   | 3598 | 3.3522          | 18.998  | 10.1323 | 18.709  | 18.5662   |
+| 2.464         | 8.0   | 4112 | 3.3314          | 18.8978 | 10.1726 | 18.5683 | 18.3049   |
+| 2.4431        | 9.0   | 4626 | 3.3508          | 18.777  | 10.3018 | 18.5103 | 18.2069   |
+| 2.4092        | 10.0  | 5140 | 3.3520          | 19.3359 | 11.2355 | 19.0265 | 18.7083   |
+| 2.4082        | 11.0  | 5654 | 3.3534          | 19.3633 | 11.2181 | 19.0465 | 18.7726   |
+| 2.3815        | 12.0  | 6168 | 3.3687          | 18.7702 | 10.395  | 18.5383 | 18.2271   |
+| 2.3706        | 13.0  | 6682 | 3.3716          | 19.0868 | 10.6534 | 18.791  | 18.5447   |
+| 2.3628        | 14.0  | 7196 | 3.3756          | 19.1222 | 10.9791 | 18.6601 | 18.5131   |
+| 2.3518        | 15.0  | 7710 | 3.3831          | 19.9227 | 11.0903 | 19.4883 | 19.2418   |
+| 2.3497        | 16.0  | 8224 | 3.3776          | 19.7803 | 11.1015 | 19.2549 | 19.0799   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3