GlycerinLOL
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README.md
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---
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license: apache-2.0
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base_model: facebook/bart-large
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tags:
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- generated_from_trainer
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datasets:
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- reddit_tifu
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metrics:
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- rouge
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- precision
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- recall
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- f1
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model-index:
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- name: Bart_reddit_tifu
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results:
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- task:
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name: Sequence-to-sequence Language Modeling
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type: text2text-generation
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dataset:
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name: reddit_tifu
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type: reddit_tifu
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config: long
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split: train
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args: long
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metrics:
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- name: Rouge1
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type: rouge
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value: 0.2709
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- name: Precision
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type: precision
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value: 0.8768
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- name: Recall
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type: recall
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value: 0.8648
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- name: F1
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type: f1
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value: 0.8705
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Bart_reddit_tifu
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the reddit_tifu dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5035
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- Rouge1: 0.2709
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- Rouge2: 0.0948
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- Rougel: 0.2244
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- Rougelsum: 0.2244
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- Gen Len: 19.3555
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- Precision: 0.8768
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- Recall: 0.8648
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- F1: 0.8705
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
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| 2.6968 | 1.0 | 2370 | 2.5385 | 0.2634 | 0.0907 | 0.218 | 0.2182 | 19.4438 | 0.8766 | 0.8641 | 0.8701 |
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| 2.4746 | 2.0 | 4741 | 2.5077 | 0.273 | 0.0941 | 0.2238 | 0.2239 | 19.2572 | 0.8774 | 0.8655 | 0.8712 |
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| 2.3066 | 3.0 | 7111 | 2.5012 | 0.2671 | 0.0936 | 0.221 | 0.2211 | 19.3071 | 0.8756 | 0.864 | 0.8696 |
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| 2.2041 | 4.0 | 9480 | 2.5035 | 0.2709 | 0.0948 | 0.2244 | 0.2244 | 19.3555 | 0.8768 | 0.8648 | 0.8705 |
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### Framework versions
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- Transformers 4.36.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.15.0
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generation_config.json
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{
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"early_stopping": true,
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"eos_token_id": 2,
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"forced_bos_token_id": 0,
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"forced_eos_token_id": 2,
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"no_repeat_ngram_size": 3,
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"num_beams": 4,
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"pad_token_id": 1,
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"transformers_version": "4.36.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1625426996
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version https://git-lfs.github.com/spec/v1
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size 1625426996
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runs/Feb03_17-57-54_o8amirctr1706761897220-scx9w/events.out.tfevents.1706954280.o8amirctr1706761897220-scx9w.31420.0
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size 11401
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