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README.md

@@ -5,7 +5,7 @@ tags:
 - generated_from_trainer
 base_model: deepseek-ai/deepseek-coder-6.7b-instruct
 model-index:
-- name: outputs/axolotl-qlora-out-code-ir-dscoder
+- name: outputs/dscoder-code-ir-2
   results: []
 ---
 
@@ -28,65 +28,67 @@ strict: false
 datasets:
   - path: vdaita/editpackft_inst_code
     type: oasst
-dataset_prepared_path: 
+dataset_prepared_path:
 val_set_size: 0.05
-output_dir: ./outputs/axolotl-qlora-out-code-ir-dscoder
+output_dir: ./outputs/dscoder-code-ir-2
 
-adapter: lora
-lora_model_dir: 
-
-sequence_len: 2048
+sequence_len: 4096
 sample_packing: true
-eval_sample_packing: false
 pad_to_sequence_len: true
 
+eval_sample_packing: false
+
+adapter: lora
+lora_model_dir:
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
-lora_target_modules: 
-  - q_proj
-  - v_proj
-  - k_proj
-  - o_proj
-  - gate_proj
-  - down_proj
-  - up_proj
 lora_target_linear: true
-lora_fan_in_fan_out: 
+lora_fan_in_fan_out:
 
 wandb_project: huggingface
-wandb_log_model: axolotl-qlora-code-dscoder
+wandb_log_model: axolotl-dscoder-code-2
 
 gradient_accumulation_steps: 4
 micro_batch_size: 2
-num_epochs: 2
-optimizer: paged_adamw_32bit
+num_epochs: 1
+optimizer: adamw_bnb_8bit
 lr_scheduler: cosine
 learning_rate: 0.0002
 
 train_on_inputs: false
 group_by_length: false
 bf16: auto
-fp16: 
+fp16:
 tf32: false
 
 gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
 logging_steps: 1
+xformers_attention:
 flash_attention: true
+s2_attention:
 
-warmup_steps: 20
-evals_per_epoch: 2
-saves_per_epoch: 2
+warmup_steps: 10
+evals_per_epoch: 4
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
 
 ```
 
 </details><br>
 
-# outputs/axolotl-qlora-out-code-ir-dscoder
+# outputs/dscoder-code-ir-2
 
 This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1829
+- Loss: 0.2242
 
 ## Model description
 
@@ -116,18 +118,17 @@ The following hyperparameters were used during training:
 - total_eval_batch_size: 4
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 20
-- num_epochs: 2
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| 0.6574        | 0.01  | 1    | 0.7462          |
-| 0.1778        | 0.5   | 39   | 0.2123          |
-| 0.2121        | 1.0   | 78   | 0.1900          |
-| 0.2512        | 1.47  | 117  | 0.1842          |
-| 0.2024        | 1.97  | 156  | 0.1829          |
+| 0.6668        | 0.03  | 1    | 0.7461          |
+| 0.5084        | 0.26  | 10   | 0.4586          |
+| 0.241         | 0.53  | 20   | 0.2486          |
+| 0.2553        | 0.79  | 30   | 0.2242          |
 
 
 ### Framework versions

adapter_config.json

@@ -20,13 +20,13 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "o_proj",
-    "q_proj",
+    "k_proj",
     "v_proj",
-    "gate_proj",
     "up_proj",
+    "gate_proj",
+    "o_proj",
     "down_proj",
-    "k_proj"
+    "q_proj"
   ],
   "task_type": "CAUSAL_LM",
   "use_dora": false,

adapter_model.bin

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checkpoint-37/README.md

@@ -0,0 +1,202 @@
+---
+library_name: peft
+base_model: deepseek-ai/deepseek-coder-6.7b-instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.10.0

checkpoint-37/adapter_config.json

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+  "base_model_name_or_path": "deepseek-ai/deepseek-coder-6.7b-instruct",
+  "bias": "none",
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+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
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+    "v_proj",
+    "up_proj",
+    "gate_proj",
+    "o_proj",
+    "down_proj",
+    "q_proj"
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+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

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+}

checkpoint-37/tokenizer_config.json

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+}

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