Instructions to use ucla-cmllab/llama-3-qlora-ultrachat-200k-processed-indicator-0.6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ucla-cmllab/llama-3-qlora-ultrachat-200k-processed-indicator-0.6 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
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---
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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: meta-llama/Meta-Llama-3-8B
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datasets:
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- yihanwang617/ultrachat_200k_processed_indicator_0.6_4k
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model-index:
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- name: llama-3-qlora-ultrachat-200k-processed-indicator-0.6
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results: []
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# llama-3-qlora-ultrachat-200k-processed-indicator-0.6
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on
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It achieves the following results on the evaluation set:
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- Loss: 1.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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### Framework versions
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---
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base_model: meta-llama/Meta-Llama-3-8B
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library_name: peft
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license: llama3
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tags:
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- trl
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- sft
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- alignment-handbook
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- generated_from_trainer
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model-index:
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- name: llama-3-qlora-ultrachat-200k-processed-indicator-0.6
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results: []
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# llama-3-qlora-ultrachat-200k-processed-indicator-0.6
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0200
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.0614 | 0.0616 | 200 | 1.0632 |
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| 1.0689 | 0.1232 | 400 | 1.0476 |
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| 1.0053 | 0.1847 | 600 | 1.0413 |
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| 1.0446 | 0.2463 | 800 | 1.0366 |
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| 1.0091 | 0.3079 | 1000 | 1.0336 |
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| 1.0093 | 0.3695 | 1200 | 1.0310 |
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| 1.0086 | 0.4311 | 1400 | 1.0291 |
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| 1.0362 | 0.4926 | 1600 | 1.0270 |
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| 1.0155 | 0.5542 | 1800 | 1.0256 |
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| 1.0138 | 0.6158 | 2000 | 1.0240 |
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| 1.0392 | 0.6774 | 2200 | 1.0226 |
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| 1.0079 | 0.7389 | 2400 | 1.0216 |
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| 1.0139 | 0.8005 | 2600 | 1.0208 |
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| 0.9857 | 0.8621 | 2800 | 1.0204 |
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| 1.0258 | 0.9237 | 3000 | 1.0201 |
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| 1.0147 | 0.9853 | 3200 | 1.0200 |
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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": 23109,
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"eval_samples_per_second": 6.137,
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"eval_steps_per_second": 0.384,
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"total_flos":
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"train_loss":
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"train_runtime":
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"train_samples": 207864,
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"train_samples_per_second": 1.
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"train_steps_per_second": 0.
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}
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"eval_samples": 23109,
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"eval_samples_per_second": 6.137,
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"eval_steps_per_second": 0.384,
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"total_flos": 3.805052032096666e+16,
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"train_loss": 0.6459755006114042,
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"train_runtime": 124690.9481,
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"train_samples": 207864,
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"train_samples_per_second": 1.667,
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"train_steps_per_second": 0.026
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}
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runs/Aug24_00-16-04_nova.cs.ucla.edu/events.out.tfevents.1724484907.nova.cs.ucla.edu.2225210.0
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train_results.json
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"train_samples_per_second": 1.
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"train_steps_per_second": 0.
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}
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{
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"epoch": 0.9997305930800908,
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"total_flos": 3.805052032096666e+16,
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"train_loss": 0.6459755006114042,
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"train_runtime": 124690.9481,
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"train_samples": 207864,
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"train_samples_per_second": 1.667,
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"train_steps_per_second": 0.026
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}
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trainer_state.json
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