JohnDoe70/t5-base-finetuned-amazon-en-es
By JohnDoe70 · ↓ 2 · ♥ 0 · Updated 2024-04-15
What's in this repo
This page lists the files in JohnDoe70/t5-base-finetuned-amazon-en-es, including decoder_model.onnx, decoder_model_merged.onnx, decoder_with_past_model.onnx and more.
- 4 ONNX models (.onnx files)
- 15 files, including 5 .json, 4 .onnx, 1 .md, 1 .safetensors, 1 .0, 1 .model
- Last updated 2024-04-15
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model.onnx | — | Download |
| onnx/decoder_model_merged.onnx | — | Download |
| onnx/decoder_with_past_model.onnx | — | Download |
| onnx/encoder_model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
t5-base-finetuned-amazon-en-es
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1275
- Rouge1: 90.2312
- Rouge2: 83.2787
- Rougel: 88.0196
- Rougelsum: 87.9916
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.113 | 1.0 | 97 | 0.1067 | 90.4949 | 83.4088 | 87.98 | 87.9287 |
| 0.0856 | 2.0 | 194 | 0.1052 | 90.6604 | 83.7509 | 88.1407 | 88.0726 |
| 0.0723 | 3.0 | 291 | 0.1060 | 91.4193 | 84.9487 | 88.9628 | 88.8729 |
| 0.064 | 4.0 | 388 | 0.1119 | 89.7878 | 83.0958 | 87.321 | 87.2759 |
| 0.0556 | 5.0 | 485 | 0.1156 | 90.5422 | 83.8358 | 88.4229 | 88.3887 |
| 0.0515 | 6.0 | 582 | 0.1126 | 90.4997 | 83.4321 | 88.1359 | 88.1405 |
| 0.0456 | 7.0 | 679 | 0.1158 | 90.5983 | 83.8471 | 88.5468 | 88.4302 |
| 0.0468 | 8.0 | 776 | 0.1189 | 90.3242 | 83.5413 | 88.2592 | 88.2061 |
| 0.0416 | 9.0 | 873 | 0.1225 | 90.2886 | 83.1885 | 88.0928 | 88.0366 |
| 0.0385 | 10.0 | 970 | 0.1252 | 89.8331 | 82.8606 | 87.3511 | 87.335 |
| 0.0377 | 11.0 | 1067 | 0.1269 | 89.9057 | 83.057 | 87.6798 | 87.6802 |
| 0.0368 | 12.0 | 1164 | 0.1275 | 90.2312 | 83.2787 | 88.0196 | 87.9916 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
Model info
Created: 2024-04-15
Updated: 2024-04-15
View on Hugging Face