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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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: LLM_Teached_Bart_From_Scratch
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results: []
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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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# LLM_Teached_Bart_From_Scratch
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4999
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- Rouge1: 0.4331
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- Rouge2: 0.2164
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- Rougel: 0.3724
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- Rougelsum: 0.3725
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- Gen Len: 19.9255
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- Precision: 0.9125
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- Recall: 0.8885
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- F1: 0.9002
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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: 32
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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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| No log | 1.0 | 390 | 1.5709 | 0.4119 | 0.2002 | 0.3529 | 0.3527 | 19.9709 | 0.9093 | 0.8846 | 0.8966 |
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| 1.8155 | 2.0 | 781 | 1.5361 | 0.4331 | 0.2157 | 0.3717 | 0.3717 | 19.9185 | 0.9123 | 0.8889 | 0.9003 |
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| 1.5875 | 3.0 | 1172 | 1.5030 | 0.4263 | 0.2129 | 0.3671 | 0.3673 | 19.9545 | 0.9117 | 0.8871 | 0.899 |
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| 1.4978 | 3.99 | 1560 | 1.4999 | 0.4331 | 0.2164 | 0.3724 | 0.3725 | 19.9255 | 0.9125 | 0.8885 | 0.9002 |
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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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oid sha256:
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size 1625426996
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version https://git-lfs.github.com/spec/v1
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oid sha256:7a48c0969c18fe75caf334533acb10619e57668b490a08aa414ef206d029df1e
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size 1625426996
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runs/Mar03_21-26-30_oi5vv8ctr1709312124223-tkfr5/events.out.tfevents.1709472393.oi5vv8ctr1709312124223-tkfr5.1103.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 9085
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