Mikhail Biriuchinskii
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fekpghojezpoh/sarcasm_BART_v2
Browse files
README.md
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---
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license: apache-2.0
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base_model: sshleifer/distilbart-xsum-12-3
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tags:
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- generated_from_trainer
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model-index:
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- name: sarcasm_BART_v2
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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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# sarcasm_BART_v2
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This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-3](https://huggingface.co/sshleifer/distilbart-xsum-12-3) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8877
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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: 3
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- eval_batch_size: 3
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- seed: 42
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| No log | 1.0 | 488 | 0.9496 |
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| 1.559 | 2.0 | 976 | 0.9030 |
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| 0.8131 | 3.0 | 1464 | 0.8735 |
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| 0.6286 | 4.0 | 1952 | 0.8715 |
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| 0.5382 | 5.0 | 2440 | 0.8877 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"eos_token_id": 2,
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"forced_eos_token_id": 2,
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"max_length": 62,
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"min_length": 11,
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"no_repeat_ngram_size": 3,
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"num_beams": 6,
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"pad_token_id": 1,
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"transformers_version": "4.38.2"
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}
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model.safetensors
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runs/Mar04_13-29-20_ae719a84a26c/events.out.tfevents.1709558962.ae719a84a26c.219.0
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