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autoevaluator
HF staff
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator
ffb3d20
metadata
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: ssr-base-finetuned-samsum-en
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: samsum
type: samsum
args: samsum
metrics:
- type: rouge
value: 46.7505
name: Rouge1
- task:
type: summarization
name: Summarization
dataset:
name: samsum
type: samsum
config: samsum
split: test
metrics:
- type: rouge
value: 46.2529
name: ROUGE-1
verified: true
verifyToken: >-
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- type: rouge
value: 21.3374
name: ROUGE-2
verified: true
verifyToken: >-
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- type: rouge
value: 36.1939
name: ROUGE-L
verified: true
verifyToken: >-
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- type: rouge
value: 42.2937
name: ROUGE-LSUM
verified: true
verifyToken: >-
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- type: loss
value: 2.0463898181915283
name: loss
verified: true
verifyToken: >-
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- type: gen_len
value: 31.3724
name: gen_len
verified: true
verifyToken: >-
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ssr-base-finetuned-samsum-en
This model is a fine-tuned version of microsoft/ssr-base on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.6231
- Rouge1: 46.7505
- Rouge2: 22.3968
- Rougel: 37.1784
- Rougelsum: 42.891
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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
1.9682 | 1.0 | 300 | 1.6432 | 44.2182 | 20.8486 | 35.0914 | 40.9852 |
1.6475 | 2.0 | 600 | 1.5946 | 45.3919 | 21.6955 | 36.2411 | 41.8532 |
1.5121 | 3.0 | 900 | 1.5737 | 46.1769 | 22.4178 | 36.9762 | 42.6614 |
1.4112 | 4.0 | 1200 | 1.5774 | 46.6047 | 22.8227 | 37.2457 | 43.1935 |
1.323 | 5.0 | 1500 | 1.5825 | 46.6162 | 22.485 | 37.2846 | 42.9834 |
1.2613 | 6.0 | 1800 | 1.5883 | 46.4253 | 22.1199 | 37.0491 | 42.5189 |
1.2077 | 7.0 | 2100 | 1.5965 | 46.485 | 22.3636 | 37.2677 | 42.7499 |
1.1697 | 8.0 | 2400 | 1.6174 | 46.8654 | 22.6291 | 37.4201 | 43.0875 |
1.1367 | 9.0 | 2700 | 1.6188 | 46.707 | 22.305 | 37.156 | 42.9087 |
1.118 | 10.0 | 3000 | 1.6231 | 46.7505 | 22.3968 | 37.1784 | 42.891 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1