
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Codellama-7b-lora-rps-adapter

This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2971

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2892        | 3.41  | 13000 | 0.3005          |
| 0.2816        | 3.42  | 13050 | 0.2992          |
| 0.2564        | 3.44  | 13100 | 0.2995          |
| 0.2596        | 3.45  | 13150 | 0.2997          |
| 0.3176        | 3.46  | 13200 | 0.2995          |
| 0.2509        | 3.48  | 13250 | 0.2992          |
| 0.3033        | 3.49  | 13300 | 0.2983          |
| 0.2797        | 3.5   | 13350 | 0.2991          |
| 0.2555        | 3.52  | 13400 | 0.2989          |
| 0.2821        | 3.53  | 13450 | 0.2984          |
| 0.2697        | 3.54  | 13500 | 0.2976          |
| 0.2505        | 3.56  | 13550 | 0.2982          |
| 0.2696        | 3.57  | 13600 | 0.2985          |
| 0.2698        | 3.58  | 13650 | 0.2973          |
| 0.2966        | 3.59  | 13700 | 0.2981          |
| 0.2468        | 3.61  | 13750 | 0.2967          |
| 0.2878        | 3.62  | 13800 | 0.2969          |
| 0.2876        | 3.63  | 13850 | 0.2984          |
| 0.2584        | 3.65  | 13900 | 0.2973          |
| 0.2677        | 3.66  | 13950 | 0.2975          |
| 0.2923        | 3.67  | 14000 | 0.2969          |
| 0.2643        | 3.69  | 14050 | 0.2968          |
| 0.2673        | 3.7   | 14100 | 0.2982          |
| 0.3016        | 3.71  | 14150 | 0.2967          |
| 0.2707        | 3.73  | 14200 | 0.2968          |
| 0.2606        | 3.74  | 14250 | 0.2976          |
| 0.2957        | 3.75  | 14300 | 0.2963          |
| 0.2509        | 3.77  | 14350 | 0.2965          |
| 0.2713        | 3.78  | 14400 | 0.2950          |
| 0.3041        | 3.79  | 14450 | 0.2968          |
| 0.265         | 3.8   | 14500 | 0.2953          |
| 0.2726        | 3.82  | 14550 | 0.2955          |
| 0.2671        | 3.83  | 14600 | 0.2957          |
| 0.2674        | 3.84  | 14650 | 0.2952          |
| 0.2516        | 3.86  | 14700 | 0.2959          |
| 0.2535        | 3.87  | 14750 | 0.2944          |
| 0.2452        | 3.88  | 14800 | 0.2945          |
| 0.2733        | 3.9   | 14850 | 0.2945          |
| 0.2718        | 3.91  | 14900 | 0.2947          |
| 0.257         | 3.92  | 14950 | 0.2939          |
| 0.2418        | 3.94  | 15000 | 0.2946          |
| 0.2583        | 3.95  | 15050 | 0.2949          |
| 0.3093        | 3.96  | 15100 | 0.2939          |
| 0.2501        | 3.98  | 15150 | 0.2937          |
| 0.2715        | 3.99  | 15200 | 0.2935          |
| 0.3209        | 4.0   | 15250 | 0.2930          |
| 0.2655        | 4.01  | 15300 | 0.2964          |
| 0.2531        | 4.03  | 15350 | 0.2963          |
| 0.2417        | 4.04  | 15400 | 0.2967          |
| 0.2574        | 4.05  | 15450 | 0.2956          |
| 0.2738        | 4.07  | 15500 | 0.2980          |
| 0.2488        | 4.08  | 15550 | 0.2967          |
| 0.2243        | 4.09  | 15600 | 0.2976          |
| 0.2414        | 4.11  | 15650 | 0.2987          |
| 0.2318        | 4.12  | 15700 | 0.2978          |
| 0.2428        | 4.13  | 15750 | 0.2963          |
| 0.2464        | 4.15  | 15800 | 0.3004          |
| 0.2717        | 4.16  | 15850 | 0.2971          |
| 0.2233        | 4.17  | 15900 | 0.2977          |
| 0.2308        | 4.19  | 15950 | 0.2980          |
| 0.2387        | 4.2   | 16000 | 0.2967          |
| 0.2305        | 4.21  | 16050 | 0.2980          |
| 0.2537        | 4.22  | 16100 | 0.2974          |
| 0.2893        | 4.24  | 16150 | 0.2974          |
| 0.2403        | 4.25  | 16200 | 0.2987          |
| 0.218         | 4.26  | 16250 | 0.2970          |
| 0.2447        | 4.28  | 16300 | 0.2963          |
| 0.2334        | 4.29  | 16350 | 0.2975          |
| 0.2481        | 4.3   | 16400 | 0.2980          |
| 0.2374        | 4.32  | 16450 | 0.2986          |
| 0.2207        | 4.33  | 16500 | 0.2968          |
| 0.2746        | 4.34  | 16550 | 0.2968          |
| 0.2262        | 4.36  | 16600 | 0.2962          |
| 0.2625        | 4.37  | 16650 | 0.2966          |
| 0.2946        | 4.38  | 16700 | 0.2969          |
| 0.2745        | 4.4   | 16750 | 0.2990          |
| 0.2418        | 4.41  | 16800 | 0.2973          |
| 0.2501        | 4.42  | 16850 | 0.2964          |
| 0.2295        | 4.43  | 16900 | 0.2970          |
| 0.2558        | 4.45  | 16950 | 0.2966          |
| 0.2577        | 4.46  | 17000 | 0.2967          |
| 0.2307        | 4.47  | 17050 | 0.2965          |
| 0.2276        | 4.49  | 17100 | 0.2965          |
| 0.2574        | 4.5   | 17150 | 0.2963          |
| 0.2668        | 4.51  | 17200 | 0.2956          |
| 0.2327        | 4.53  | 17250 | 0.2977          |
| 0.254         | 4.54  | 17300 | 0.2951          |
| 0.2511        | 4.55  | 17350 | 0.2949          |
| 0.2176        | 4.57  | 17400 | 0.2953          |
| 0.2294        | 4.58  | 17450 | 0.2962          |
| 0.2588        | 4.59  | 17500 | 0.2951          |
| 0.2903        | 4.61  | 17550 | 0.2946          |
| 0.2326        | 4.62  | 17600 | 0.2946          |
| 0.2508        | 4.63  | 17650 | 0.2945          |
| 0.251         | 4.64  | 17700 | 0.2949          |
| 0.2281        | 4.66  | 17750 | 0.2954          |
| 0.2265        | 4.67  | 17800 | 0.2958          |
| 0.23          | 4.68  | 17850 | 0.2955          |
| 0.2489        | 4.7   | 17900 | 0.2946          |
| 0.2373        | 4.71  | 17950 | 0.2945          |
| 0.2365        | 4.72  | 18000 | 0.2948          |
| 0.245         | 4.74  | 18050 | 0.2941          |
| 0.2597        | 4.75  | 18100 | 0.2949          |
| 0.2325        | 4.76  | 18150 | 0.2946          |
| 0.2495        | 4.78  | 18200 | 0.2946          |
| 0.2583        | 4.79  | 18250 | 0.2949          |
| 0.2162        | 4.8   | 18300 | 0.2945          |
| 0.2292        | 4.82  | 18350 | 0.2941          |
| 0.2695        | 4.83  | 18400 | 0.2943          |
| 0.2602        | 4.84  | 18450 | 0.2934          |
| 0.2179        | 4.85  | 18500 | 0.2947          |
| 0.2356        | 4.87  | 18550 | 0.2930          |
| 0.2692        | 4.88  | 18600 | 0.2936          |
| 0.2627        | 4.89  | 18650 | 0.2935          |
| 0.2476        | 4.91  | 18700 | 0.2947          |
| 0.2529        | 4.92  | 18750 | 0.2924          |
| 0.2358        | 4.93  | 18800 | 0.2920          |
| 0.232         | 4.95  | 18850 | 0.2930          |
| 0.2439        | 4.96  | 18900 | 0.2928          |
| 0.2355        | 4.97  | 18950 | 0.2926          |
| 0.2489        | 4.99  | 19000 | 0.2926          |
| 0.2777        | 5.0   | 19050 | 0.2924          |
| 0.2384        | 5.01  | 19100 | 0.2976          |
| 0.2201        | 5.02  | 19150 | 0.2990          |
| 0.2065        | 5.04  | 19200 | 0.2976          |
| 0.2138        | 5.05  | 19250 | 0.2963          |
| 0.2367        | 5.06  | 19300 | 0.2973          |
| 0.2319        | 5.08  | 19350 | 0.2985          |
| 0.2199        | 5.09  | 19400 | 0.2991          |
| 0.212         | 5.1   | 19450 | 0.2989          |
| 0.2085        | 5.12  | 19500 | 0.2983          |
| 0.1995        | 5.13  | 19550 | 0.2986          |
| 0.2333        | 5.14  | 19600 | 0.2979          |
| 0.2286        | 5.16  | 19650 | 0.2989          |
| 0.215         | 5.17  | 19700 | 0.2977          |
| 0.2417        | 5.18  | 19750 | 0.2977          |
| 0.211         | 5.2   | 19800 | 0.2983          |
| 0.2132        | 5.21  | 19850 | 0.2996          |
| 0.2079        | 5.22  | 19900 | 0.3001          |
| 0.2022        | 5.23  | 19950 | 0.2988          |
| 0.2178        | 5.25  | 20000 | 0.2989          |
| 0.1975        | 5.26  | 20050 | 0.2992          |
| 0.245         | 5.27  | 20100 | 0.2979          |
| 0.256         | 5.29  | 20150 | 0.2988          |
| 0.2355        | 5.3   | 20200 | 0.3005          |
| 0.2018        | 5.31  | 20250 | 0.3001          |
| 0.2078        | 5.33  | 20300 | 0.2986          |
| 0.2128        | 5.34  | 20350 | 0.2997          |
| 0.2202        | 5.35  | 20400 | 0.2979          |
| 0.2311        | 5.37  | 20450 | 0.2988          |
| 0.2374        | 5.38  | 20500 | 0.2980          |
| 0.2617        | 5.39  | 20550 | 0.2975          |
| 0.2082        | 5.41  | 20600 | 0.2985          |
| 0.2531        | 5.42  | 20650 | 0.2984          |
| 0.2103        | 5.43  | 20700 | 0.2979          |
| 0.2569        | 5.44  | 20750 | 0.2990          |
| 0.2254        | 5.46  | 20800 | 0.2977          |
| 0.2328        | 5.47  | 20850 | 0.2971          |
| 0.2162        | 5.48  | 20900 | 0.2981          |
| 0.2373        | 5.5   | 20950 | 0.2977          |
| 0.2447        | 5.51  | 21000 | 0.2972          |
| 0.2131        | 5.52  | 21050 | 0.2976          |
| 0.2355        | 5.54  | 21100 | 0.2983          |
| 0.2327        | 5.55  | 21150 | 0.2977          |
| 0.2601        | 5.56  | 21200 | 0.2970          |
| 0.2074        | 5.58  | 21250 | 0.2977          |
| 0.2153        | 5.59  | 21300 | 0.2969          |
| 0.2072        | 5.6   | 21350 | 0.2975          |
| 0.2162        | 5.62  | 21400 | 0.2971          |
| 0.2399        | 5.63  | 21450 | 0.2969          |
| 0.2248        | 5.64  | 21500 | 0.2974          |
| 0.2608        | 5.65  | 21550 | 0.2973          |
| 0.2322        | 5.67  | 21600 | 0.2974          |
| 0.2283        | 5.68  | 21650 | 0.2983          |
| 0.1931        | 5.69  | 21700 | 0.2986          |
| 0.2341        | 5.71  | 21750 | 0.2981          |
| 0.2318        | 5.72  | 21800 | 0.2979          |
| 0.223         | 5.73  | 21850 | 0.2974          |
| 0.2075        | 5.75  | 21900 | 0.2974          |
| 0.2277        | 5.76  | 21950 | 0.2975          |
| 0.2167        | 5.77  | 22000 | 0.2976          |
| 0.1904        | 5.79  | 22050 | 0.2975          |
| 0.2049        | 5.8   | 22100 | 0.2974          |
| 0.2207        | 5.81  | 22150 | 0.2976          |
| 0.2017        | 5.83  | 22200 | 0.2972          |
| 0.2068        | 5.84  | 22250 | 0.2972          |
| 0.2453        | 5.85  | 22300 | 0.2967          |
| 0.2121        | 5.86  | 22350 | 0.2968          |
| 0.2193        | 5.88  | 22400 | 0.2971          |
| 0.2337        | 5.89  | 22450 | 0.2971          |
| 0.227         | 5.9   | 22500 | 0.2971          |
| 0.2285        | 5.92  | 22550 | 0.2972          |
| 0.2141        | 5.93  | 22600 | 0.2974          |
| 0.2269        | 5.94  | 22650 | 0.2971          |
| 0.2192        | 5.96  | 22700 | 0.2971          |
| 0.217         | 5.97  | 22750 | 0.2971          |
| 0.1998        | 5.98  | 22800 | 0.2971          |
| 0.2188        | 6.0   | 22850 | 0.2971          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
{"license": "llama2", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "codellama/CodeLlama-7b-Instruct-hf", "model-index": [{"name": "Codellama-7b-lora-rps-adapter", "results": []}]}
peft tensorboard safetensors trl sft generated_from_trainer base_model:codellama/CodeLlama-7b-Instruct-hf license:llama2 region:us