JohnDoe70/t5-summarization-v2
By JohnDoe70 · ↓ 4 · ♥ 0 · Updated 2024-05-01
What's in this repo
This page lists the files in JohnDoe70/t5-summarization-v2, including decoder_model.onnx, decoder_model_merged.onnx, decoder_model_merged_quantized.onnx and more.
- 8 ONNX models (.onnx files)
- 20 files, including 8 .onnx, 5 .json, 2 .0, 1 .md, 1 .safetensors, 1 .model
- Last updated 2024-05-01
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model.onnx | — | Download |
| onnx/decoder_model_merged.onnx | — | Download |
| onnx/decoder_model_merged_quantized.onnx | — | Download |
| onnx/decoder_model_quantized.onnx | — | Download |
| onnx/decoder_with_past_model.onnx | — | Download |
| onnx/decoder_with_past_model_quantized.onnx | — | Download |
| onnx/encoder_model.onnx | — | Download |
| onnx/encoder_model_quantized.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-question-answer-summarization
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: 0.1424
- Rouge1: 85.4974
- Rouge2: 77.0571
- Rougel: 82.4125
- Rougelsum: 82.4757
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.3381 | 1.0 | 526 | 0.1310 | 85.4136 | 77.2307 | 82.5493 | 82.5887 |
| 0.1221 | 2.0 | 1052 | 0.1291 | 85.5109 | 77.3495 | 82.5035 | 82.5448 |
| 0.1008 | 3.0 | 1578 | 0.1293 | 85.7918 | 77.3841 | 82.5218 | 82.5855 |
| 0.0861 | 4.0 | 2104 | 0.1312 | 85.8164 | 77.5711 | 82.5025 | 82.5955 |
| 0.075 | 5.0 | 2630 | 0.1358 | 85.769 | 77.3766 | 82.6532 | 82.691 |
| 0.069 | 6.0 | 3156 | 0.1361 | 85.417 | 76.9087 | 82.397 | 82.4857 |
| 0.0625 | 7.0 | 3682 | 0.1404 | 85.5539 | 77.0784 | 82.4147 | 82.445 |
| 0.0595 | 8.0 | 4208 | 0.1424 | 85.4974 | 77.0571 | 82.4125 | 82.4757 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
Model info
Created: 2024-04-29
Updated: 2024-05-01
View on Hugging Face