update model card README.md

README.md

@@ -1,20 +1,79 @@
 ---
-library_name: peft
+license: bigcode-openrail-m
+base_model: bigcode/starcoder
+tags:
+- generated_from_trainer
+model-index:
+- name: peft-lora-starcoder-personal-copilot-A100-40GB-colab
+  results: []
 ---
+
+<!-- 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. -->
+
+# peft-lora-starcoder-personal-copilot-A100-40GB-colab
+
+This model is a fine-tuned version of [bigcode/starcoder](https://huggingface.co/bigcode/starcoder) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3627
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
 ## Training procedure
 
+### Training hyperparameters
 
-The following `bitsandbytes` quantization config was used during training:
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: True
-- bnb_4bit_compute_dtype: bfloat16
-### Framework versions
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant
+- lr_scheduler_warmup_steps: 30
+- training_steps: 2000
+
+### Training results
 
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.66          | 0.05  | 100  | 0.5844          |
+| 0.6223        | 0.1   | 200  | 0.5280          |
+| 0.6601        | 0.15  | 300  | 0.4819          |
+| 0.5526        | 0.2   | 400  | 0.4617          |
+| 0.485         | 0.25  | 500  | 0.4593          |
+| 0.5239        | 0.3   | 600  | 0.4492          |
+| 0.489         | 0.35  | 700  | 0.4371          |
+| 0.5582        | 0.4   | 800  | 0.4362          |
+| 0.4688        | 0.45  | 900  | 0.4314          |
+| 0.5415        | 0.5   | 1000 | 0.4227          |
+| 0.5152        | 0.55  | 1100 | 0.4121          |
+| 0.5243        | 0.6   | 1200 | 0.3967          |
+| 0.414         | 0.65  | 1300 | 0.3954          |
+| 0.557         | 0.7   | 1400 | 0.3926          |
+| 0.4144        | 0.75  | 1500 | 0.3911          |
+| 0.7935        | 0.8   | 1600 | 0.3896          |
+| 0.4129        | 0.85  | 1700 | 0.3866          |
+| 0.4549        | 0.9   | 1800 | 0.3877          |
+| 0.3903        | 0.95  | 1900 | 0.3781          |
+| 0.4945        | 1.0   | 2000 | 0.3627          |
+
+
+### Framework versions
 
-- PEFT 0.4.0
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3