psxjp5
/

mt5-small

+---
+license: apache-2.0
+base_model: google/mt5-small
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- bleu
+model-index:
+- name: mt5-small_test_45
+  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_test_45
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7291
+- Rouge1: 44.4366
+- Rouge2: 38.8202
+- Rougel: 43.113
+- Rougelsum: 43.1423
+- Bleu: 34.1596
+- Gen Len: 12.6724
+- Meteor: 0.4049
+- True negatives: 69.7281
+- False negatives: 10.4037
+- Cosine Sim: 0.763
+## 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: 0.001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 9
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu    | Gen Len | Meteor | True negatives | False negatives | Cosine Sim |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:--------------:|:---------------:|:----------:|
+| 2.5724        | 1.0   | 175  | 0.9876          | 18.7781 | 15.6002 | 18.22   | 18.2686   | 7.6676  | 7.7661  | 0.1628 | 72.8701        | 56.677          | 0.4003     |
+| 1.1469        | 1.99  | 350  | 0.8580          | 36.8209 | 31.2514 | 35.5008 | 35.5462   | 25.7137 | 12.0014 | 0.3311 | 62.8399        | 20.3934         | 0.6645     |
+| 0.9468        | 2.99  | 525  | 0.7997          | 40.4128 | 34.716  | 39.0867 | 39.0972   | 29.3028 | 12.4287 | 0.3656 | 63.4441        | 15.295          | 0.7114     |
+| 0.8129        | 3.98  | 700  | 0.7733          | 42.6764 | 36.7266 | 41.2465 | 41.2833   | 32.0644 | 12.9002 | 0.3871 | 62.1752        | 11.413          | 0.7425     |
+| 0.7228        | 4.98  | 875  | 0.7483          | 42.9082 | 36.957  | 41.482  | 41.5233   | 32.4942 | 12.8866 | 0.3906 | 63.3233        | 11.5166         | 0.747      |
+| 0.6493        | 5.97  | 1050 | 0.7293          | 40.3205 | 34.9632 | 39.1111 | 39.1168   | 28.8249 | 11.6867 | 0.3674 | 73.8973        | 17.9865         | 0.7068     |
+| 0.5883        | 6.97  | 1225 | 0.7172          | 42.7342 | 37.0855 | 41.4069 | 41.424    | 32.1296 | 12.48   | 0.3887 | 70.0302        | 12.7847         | 0.7392     |
+| 0.5409        | 7.96  | 1400 | 0.7387          | 44.6657 | 38.8426 | 43.3276 | 43.3496   | 34.4773 | 12.9395 | 0.4084 | 66.3444        | 9.5238          | 0.7658     |
+| 0.5035        | 8.96  | 1575 | 0.7330          | 43.4925 | 38.0013 | 42.2697 | 42.2372   | 32.6131 | 12.2789 | 0.3979 | 72.6284        | 12.8364         | 0.7451     |
+| 0.4652        | 9.95  | 1750 | 0.7291          | 44.4366 | 38.8202 | 43.113  | 43.1423   | 34.1596 | 12.6724 | 0.4049 | 69.7281        | 10.4037         | 0.763      |
+### Framework versions
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3