Model save
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README.md
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---
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license: gemma
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library_name: peft
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tags:
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- trl
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- sft
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- generated_from_trainer
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base_model: google/gemma-2b
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datasets:
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- generator
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model-index:
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- name: gemma2b-summarize-claude3sonnet-64k
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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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# gemma2b-summarize-claude3sonnet-64k
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5427
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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: 0.0002
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- train_batch_size: 8
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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: 3
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 48
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- total_eval_batch_size: 24
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-------:|:----:|:---------------:|
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| 1.163 | 0.9975 | 200 | 2.5127 |
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| 1.0647 | 2.0 | 401 | 2.4643 |
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| 1.0051 | 2.9975 | 601 | 2.4610 |
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| 0.9807 | 4.0 | 802 | 2.4767 |
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| 0.9508 | 4.9975 | 1002 | 2.4788 |
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| 0.9256 | 6.0 | 1203 | 2.4912 |
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| 0.9216 | 6.9975 | 1403 | 2.5038 |
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| 0.9094 | 8.0 | 1604 | 2.5124 |
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| 0.8961 | 8.9975 | 1804 | 2.5246 |
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| 0.8816 | 10.0 | 2005 | 2.5342 |
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| 0.8722 | 10.9975 | 2205 | 2.5346 |
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| 0.8768 | 12.0 | 2406 | 2.5410 |
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| 0.8694 | 12.9975 | 2606 | 2.5415 |
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| 0.8709 | 14.0 | 2807 | 2.5418 |
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| 0.8781 | 14.9626 | 3000 | 2.5427 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.0
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- Pytorch 2.2.2+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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adapter_model.safetensors
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all_results.json
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{
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"epoch": 14.962593516209477,
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"total_flos": 1.7621200159784305e+18,
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"train_loss": 0.9822600702444713,
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"train_runtime": 10311.9233,
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"train_samples": 63494,
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"train_samples_per_second": 13.994,
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"train_steps_per_second": 0.291
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}
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runs/Jun05_15-30-52_user-HP-Z8-Fury-G5-Workstation-Desktop-PC/events.out.tfevents.1717569090.user-HP-Z8-Fury-G5-Workstation-Desktop-PC.937701.0
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size 136602
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train_results.json
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{
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"epoch": 14.962593516209477,
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"total_flos": 1.7621200159784305e+18,
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"train_loss": 0.9822600702444713,
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"train_runtime": 10311.9233,
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"train_samples": 63494,
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"train_samples_per_second": 13.994,
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"train_steps_per_second": 0.291
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}
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trainer_state.json
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