Model save
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README.md
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license: gemma
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library_name: peft
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tags:
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- alignment-handbook
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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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-
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model-index:
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- name: gemma2b-summarize-gpt4o-128k
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results: []
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# gemma2b-summarize-gpt4o-128k
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the
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It achieves the following results on the evaluation set:
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- Loss: 2.
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## Model description
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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:
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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.
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| 1.
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| 0.952 | 11.0 | 3223 | 2.5192 |
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| 0.9505 | 12.0 | 3516 | 2.5205 |
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| 0.9442 | 13.0 | 3809 | 2.5223 |
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| 0.9469 | 14.0 | 4102 | 2.5227 |
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| 0.9444 | 15.0 | 4395 | 2.5233 |
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### Framework versions
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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-gpt4o-128k
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results: []
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# gemma2b-summarize-gpt4o-128k
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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: 2.7978
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## Model description
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.1249 | 1.0 | 293 | 2.4641 |
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| 1.0415 | 2.0 | 586 | 2.4514 |
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| 0.9915 | 3.0 | 879 | 2.4750 |
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| 0.9551 | 4.0 | 1172 | 2.5292 |
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| 0.9287 | 5.0 | 1465 | 2.5925 |
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| 0.8733 | 6.0 | 1758 | 2.6555 |
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| 0.8577 | 7.0 | 2051 | 2.7316 |
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| 0.8364 | 8.0 | 2344 | 2.7742 |
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| 0.8311 | 9.0 | 2637 | 2.7971 |
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| 0.8243 | 10.0 | 2930 | 2.7978 |
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### Framework versions
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adapter_model.safetensors
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all_results.json
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"eval_samples_per_second": 18.753,
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"eval_steps_per_second": 1.875,
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"total_flos": 2.581505823377195e+18,
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"train_loss": 1.0488379673203783,
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"train_runtime": 23446.7186,
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"train_samples": 129221,
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"train_samples_per_second":
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"train_steps_per_second": 0.
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"epoch": 10.0,
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"total_flos": 1.7464232891960525e+18,
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"train_loss": 0.9647074054125633,
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"train_runtime": 17674.2713,
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"train_samples": 129221,
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"train_samples_per_second": 7.945,
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"train_steps_per_second": 0.166
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}
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runs/Jun10_18-07-27_user-HP-Z8-Fury-G5-Workstation-Desktop-PC/events.out.tfevents.1718010465.user-HP-Z8-Fury-G5-Workstation-Desktop-PC.8637.0
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size 132418
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train_results.json
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"total_flos":
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"train_loss":
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"train_samples": 129221,
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"train_steps_per_second": 0.
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"epoch": 10.0,
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"total_flos": 1.7464232891960525e+18,
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"train_loss": 0.9647074054125633,
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"train_runtime": 17674.2713,
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"train_samples": 129221,
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"train_samples_per_second": 7.945,
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"train_steps_per_second": 0.166
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}
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trainer_state.json
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