update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- summarization
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: mt5-small-text-sum-2
+  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. -->
+
+# mt5-small-text-sum-2
+
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3612
+- Rouge1: 21.38
+- Rouge2: 6.57
+- Rougel: 21.08
+
+## 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: 0.0001
+- train_batch_size: 9
+- eval_batch_size: 9
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
+| 4.7204        | 1.45  | 500   | 2.6053          | 16.9   | 4.9    | 16.73  |
+| 3.1289        | 2.9   | 1000  | 2.4878          | 17.96  | 5.26   | 17.82  |
+| 2.8862        | 4.35  | 1500  | 2.4109          | 17.4   | 5.08   | 17.14  |
+| 2.7669        | 5.8   | 2000  | 2.4006          | 18.53  | 5.29   | 18.21  |
+| 2.6433        | 7.25  | 2500  | 2.4017          | 18.69  | 5.71   | 18.53  |
+| 2.5514        | 8.7   | 3000  | 2.3917          | 19.32  | 5.89   | 19.12  |
+| 2.4947        | 10.14 | 3500  | 2.3994          | 20.56  | 6.08   | 20.19  |
+| 2.3995        | 11.59 | 4000  | 2.3608          | 20.11  | 6.52   | 19.75  |
+| 2.3798        | 13.04 | 4500  | 2.3251          | 19.98  | 6.26   | 19.76  |
+| 2.3029        | 14.49 | 5000  | 2.3387          | 19.71  | 6.11   | 19.42  |
+| 2.2563        | 15.94 | 5500  | 2.3372          | 20.18  | 6.34   | 19.8   |
+| 2.2109        | 17.39 | 6000  | 2.3410          | 20.58  | 6.35   | 20.14  |
+| 2.166         | 18.84 | 6500  | 2.3432          | 20.93  | 6.5    | 20.63  |
+| 2.1283        | 20.29 | 7000  | 2.3404          | 21.0   | 6.5    | 20.73  |
+| 2.1054        | 21.74 | 7500  | 2.3563          | 20.95  | 6.54   | 20.48  |
+| 2.0658        | 23.19 | 8000  | 2.3575          | 19.73  | 6.18   | 19.54  |
+| 2.0461        | 24.64 | 8500  | 2.3382          | 20.78  | 6.42   | 20.52  |
+| 2.0135        | 26.09 | 9000  | 2.3628          | 20.94  | 6.55   | 20.66  |
+| 2.0122        | 27.54 | 9500  | 2.3725          | 21.1   | 6.87   | 20.96  |
+| 1.9623        | 28.99 | 10000 | 2.3612          | 21.38  | 6.57   | 21.08  |
+| 1.9518        | 30.43 | 10500 | 2.3619          | 20.12  | 6.25   | 19.8   |
+| 1.9327        | 31.88 | 11000 | 2.3642          | 20.9   | 6.6    | 20.55  |
+| 1.9147        | 33.33 | 11500 | 2.3703          | 21.0   | 6.37   | 20.59  |
+| 1.9145        | 34.78 | 12000 | 2.3823          | 21.24  | 6.84   | 20.92  |
+| 1.9065        | 36.23 | 12500 | 2.3686          | 20.16  | 6.41   | 19.87  |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2