AdamCodd/bart-large-cnn-samsum
By AdamCodd · ↓ 4 · ♥ 2 · Updated 2023-11-17
What's in this repo
This page lists the files in AdamCodd/bart-large-cnn-samsum, including decoder_model.onnx, decoder_model_merged.onnx, decoder_with_past_model.onnx and more.
- 4 ONNX models (.onnx files)
- 24 files, including 13 .json, 4 .onnx, 2 .txt, 2 .bin, 1 .md, 1 .safetensors
- Last updated 2023-11-17
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
bart-large-cnn-samsum
This model is a fine-tuned version of facebook/bart-large-cnn on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 0.755
- Rouge1: 43.6283
- Rouge2: 19.3096
- Rougel: 41.2140
- Rougelsum: 37.2590
Model description
More information needed
Intended uses & limitations
from transformers import pipeline
summarizer = pipeline("summarization", model="AdamCodd/bart-large-cnn-samsum")
conversation = '''Emily: Hey Alex, have you heard about the new restaurant that opened downtown?
Alex: No, I haven't. What's it called?
Emily: It's called "Savory Bites." They say it has the best pasta in town.
Alex: That sounds delicious. When are you thinking of checking it out?
Emily: How about this Saturday? We can make it a dinner date.
Alex: Sounds like a plan, Emily. I'm looking forward to it.
'''
result = summarizer(conversation)
print(result)
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1270
- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- num_epochs: 1
Training results
| key | value |
|---|---|
| eval_rouge1 | 43.6283 |
| eval_rouge2 | 19.3096 |
| eval_rougeL | 41.2140 |
| eval_rougeLsum | 37.2590 |
Framework versions
- Transformers 4.34.0
- Pytorch lightning 2.0.9
- Tokenizers 0.14.0
If you want to support me, you can here.
Model info
Created: 2023-10-04
Updated: 2023-11-17
View on Hugging Face