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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: kykim0/pythia-1b-tulu-v2-mix
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - allenai/ultrafeedback_binarized_cleaned
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: b32-lr1.41e-05-s0-e2-btbinf-seed42
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: allenai/ultrafeedback_binarized_cleaned
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+ type: allenai/ultrafeedback_binarized_cleaned
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7427109974424553
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+ ---
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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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+
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+ # b32-lr1.41e-05-s0-e2-btbinf-seed42
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+
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+ This model is a fine-tuned version of [kykim0/pythia-1b-tulu-v2-mix](https://huggingface.co/kykim0/pythia-1b-tulu-v2-mix) on the allenai/ultrafeedback_binarized_cleaned dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5040
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+ - Accuracy: 0.7458
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1.41e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 32
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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: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.6627 | 0.0527 | 100 | 0.6306 | 0.6675 |
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+ | 0.5604 | 0.1055 | 200 | 0.5954 | 0.6890 |
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+ | 0.5743 | 0.1582 | 300 | 0.5773 | 0.6880 |
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+ | 0.573 | 0.2110 | 400 | 0.5408 | 0.7182 |
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+ | 0.5644 | 0.2637 | 500 | 0.5285 | 0.7361 |
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+ | 0.5482 | 0.3165 | 600 | 0.5251 | 0.7366 |
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+ | 0.5673 | 0.3692 | 700 | 0.5267 | 0.7279 |
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+ | 0.5701 | 0.4219 | 800 | 0.5123 | 0.7453 |
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+ | 0.5199 | 0.4747 | 900 | 0.5148 | 0.7376 |
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+ | 0.5525 | 0.5274 | 1000 | 0.5133 | 0.7494 |
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+ | 0.5197 | 0.5802 | 1100 | 0.5085 | 0.7488 |
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+ | 0.4977 | 0.6329 | 1200 | 0.5146 | 0.7412 |
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+ | 0.492 | 0.6857 | 1300 | 0.5116 | 0.7417 |
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+ | 0.5046 | 0.7384 | 1400 | 0.5069 | 0.7453 |
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+ | 0.5476 | 0.7911 | 1500 | 0.5044 | 0.7478 |
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+ | 0.5247 | 0.8439 | 1600 | 0.5038 | 0.7468 |
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+ | 0.5591 | 0.8966 | 1700 | 0.5079 | 0.7453 |
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+ | 0.5228 | 0.9494 | 1800 | 0.5040 | 0.7458 |
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+ | 0.5336 | 1.0021 | 1900 | 0.5045 | 0.7488 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.19.1
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