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
test-dialogue-summarization
This model is a fine-tuned version of 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