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mt5-small_25
psxjp5/mt5-small_25
mt5-small_25 is a machine learning model from psxjp5. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Aug 8, 2023
- Updated
- Aug 8, 2023
- SHA
- fa027d07
Base models
Model card
From the Hugging Face model README
<!-- 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
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7284
- Rouge1: 43.3718
- Rouge2: 37.5973
- Rougel: 42.0502
- Rougelsum: 42.0648
- Bleu: 32.8345
- Gen Len: 12.6063
- Meteor: 0.3949
- True negatives: 70.2115
- False negatives: 11.206
- Cosine Sim: 0.7485
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3.1455 | 1.0 | 175 | 0.9832 | 18.7269 | 15.517 | 18.22 | 18.223 | 7.0634 | 7.6229 | 0.1626 | 74.6828 | 57.1687 | 0.3949 |
| 1.1623 | 1.99 | 350 | 0.8542 | 38.7603 | 32.7237 | 37.3447 | 37.3752 | 27.4323 | 12.5135 | 0.3487 | 60.0 | 15.942 | 0.6992 |
| 0.9431 | 2.99 | 525 | 0.8017 | 41.5759 | 35.6108 | 40.2536 | 40.2695 | 30.7994 | 12.8117 | 0.3755 | 61.2689 | 12.3447 | 0.7304 |
| 0.8119 | 3.98 | 700 | 0.7787 | 43.5881 | 37.4245 | 42.1096 | 42.1248 | 32.9646 | 13.2176 | 0.3947 | 59.1541 | 9.5238 | 0.7582 |
| 0.7235 | 4.98 | 875 | 0.7477 | 43.4069 | 37.2246 | 41.8444 | 41.8616 | 32.9345 | 13.116 | 0.3946 | 63.0816 | 9.8085 | 0.7561 |
| 0.6493 | 5.97 | 1050 | 0.7266 | 40.4506 | 35.0072 | 39.1206 | 39.1181 | 29.0601 | 11.748 | 0.3687 | 75.5287 | 17.2101 | 0.7071 |
| 0.5871 | 6.97 | 1225 | 0.7284 | 43.3718 | 37.5973 | 42.0502 | 42.0648 | 32.8345 | 12.6063 | 0.3949 | 70.2115 | 11.206 | 0.7485 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Aug 8, 2023
- Updated
- Aug 8, 2023