End of training

README.md

@@ -6,7 +6,6 @@ tags:
 model-index:
 - name: peft-lora-starcoder15B-v2-personal-copilot-A100-40GB-colab
   results: []
-library_name: peft
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.3700
+- Loss: 0.3096
 
 ## Model description
 
@@ -32,18 +31,6 @@ More information needed
 
 ## Training procedure
 
-
-The following `bitsandbytes` quantization config was used during training:
-- quant_method: bitsandbytes
-- 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
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -56,27 +43,36 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_steps: 30
-- training_steps: 1000
+- training_steps: 2000
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| 0.6438        | 0.1   | 100  | 0.5596          |
-| 0.5992        | 0.2   | 200  | 0.4886          |
-| 0.6327        | 0.3   | 300  | 0.4319          |
-| 0.5269        | 0.4   | 400  | 0.4077          |
-| 0.4533        | 0.5   | 500  | 0.3990          |
-| 0.4755        | 0.6   | 600  | 0.3852          |
-| 0.4445        | 0.7   | 700  | 0.3735          |
-| 0.5179        | 0.8   | 800  | 0.3721          |
-| 0.4185        | 0.9   | 900  | 0.3706          |
-| 0.4807        | 1.0   | 1000 | 0.3700          |
+| 0.6439        | 0.05  | 100  | 0.5595          |
+| 0.6009        | 0.1   | 200  | 0.4901          |
+| 0.6335        | 0.15  | 300  | 0.4320          |
+| 0.5266        | 0.2   | 400  | 0.4082          |
+| 0.4543        | 0.25  | 500  | 0.4012          |
+| 0.4808        | 0.3   | 600  | 0.3911          |
+| 0.461         | 0.35  | 700  | 0.4364          |
+| 0.5246        | 0.4   | 800  | 0.3720          |
+| 0.408         | 0.45  | 900  | 0.3655          |
+| 0.469         | 0.5   | 1000 | 0.3504          |
+| 0.4257        | 0.55  | 1100 | 0.3396          |
+| 0.4229        | 0.6   | 1200 | 0.3195          |
+| 0.3267        | 0.65  | 1300 | 0.3147          |
+| 0.4682        | 0.7   | 1400 | 0.3110          |
+| 0.3244        | 0.75  | 1500 | 0.3091          |
+| 0.6782        | 0.8   | 1600 | 0.3085          |
+| 0.3123        | 0.85  | 1700 | 0.3084          |
+| 0.3545        | 0.9   | 1800 | 0.3094          |
+| 0.2818        | 0.95  | 1900 | 0.3095          |
+| 0.397         | 1.0   | 2000 | 0.3096          |
 
 
 ### Framework versions
 
-- PEFT 0.5.0.dev0
 - Transformers 4.32.0.dev0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.4