File size: 1,937 Bytes
be67b9a 116de86 1af2083 fa5abff 116de86 871bf26 116de86 871bf26 116de86 871bf26 116de86 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: test-dialogue-summarization
results: []
pipeline_tag: summarization
library_name: transformers
---
<!-- 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. -->
# test-dialogue-summarization
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
eval_loss: 0.8548385500907898,
eval_rouge1: 66.4768,
eval_rouge2: 48.5059,
eval_rougeL: 55.6107,
eval_rougeLsum: 64.379,
eval_gen_len: 135.19,
eval_runtime: 106.4023,
eval_samples_per_second: 0.94,
eval_steps_per_second: 0.235,
epoch: 5.0
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
Epoch Training Loss Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1 No log 0.968213 59.682700 35.068600 44.651000 56.618200 137.666700
2 No log 0.961468 61.080300 37.609500 47.390200 58.380500 134.193300
3 No log 0.965955 62.082900 39.734400 48.736800 59.302500 135.833300
4 No log 0.975513 63.494900 42.147500 50.690800 60.831800 134.246700
5 No log 0.983745 64.556600 43.555200 51.977700 61.979700 134.180000
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3 |