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license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: mt5-small_test_35
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_35
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: 0.7383
- Rouge1: 43.9482
- Rouge2: 38.4156
- Rougel: 42.6232
- Rougelsum: 42.674
- Bleu: 33.3469
- Gen Len: 12.4725
- Meteor: 0.4016
- True negatives: 70.997
- False negatives: 11.8271
- Cosine Sim: 0.7532
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:--------------:|:---------------:|:----------:|
| 2.4524 | 1.0 | 175 | 0.9783 | 17.6419 | 14.587 | 17.1176 | 17.1329 | 6.1296 | 7.3271 | 0.1531 | 75.7704 | 59.8602 | 0.3786 |
| 1.1433 | 1.99 | 350 | 0.8448 | 38.9957 | 33.2414 | 37.7868 | 37.8653 | 27.5883 | 12.3274 | 0.3526 | 60.3625 | 17.236 | 0.6954 |
| 0.9381 | 2.99 | 525 | 0.8067 | 42.4146 | 36.3126 | 40.964 | 41.0427 | 31.5838 | 13.0716 | 0.3833 | 59.6375 | 11.1801 | 0.7425 |
| 0.8116 | 3.98 | 700 | 0.7712 | 43.8741 | 37.8446 | 42.3785 | 42.4778 | 33.1873 | 13.0574 | 0.3982 | 61.9335 | 9.5238 | 0.7586 |
| 0.7218 | 4.98 | 875 | 0.7439 | 43.1579 | 37.3057 | 41.7059 | 41.8024 | 32.5124 | 12.7853 | 0.3931 | 65.8006 | 11.2836 | 0.7498 |
| 0.6461 | 5.97 | 1050 | 0.7254 | 39.9226 | 34.552 | 38.7033 | 38.7665 | 27.9936 | 11.4675 | 0.3638 | 77.9456 | 18.5041 | 0.7003 |
| 0.5852 | 6.97 | 1225 | 0.7290 | 44.131 | 38.3527 | 42.7974 | 42.8549 | 33.6955 | 12.7811 | 0.4026 | 67.855 | 10.3778 | 0.7599 |
| 0.5421 | 7.96 | 1400 | 0.7248 | 44.5368 | 38.7443 | 43.2111 | 43.2976 | 34.1121 | 12.7875 | 0.4071 | 67.5529 | 10.4037 | 0.7637 |
| 0.5026 | 8.96 | 1575 | 0.7383 | 43.9482 | 38.4156 | 42.6232 | 42.674 | 33.3469 | 12.4725 | 0.4016 | 70.997 | 11.8271 | 0.7532 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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