Update README.md

README.md

@@ -1,139 +1,4 @@
----
-license: llama2
-base_model: codellama/CodeLlama-7b-hf
-tags:
-- generated_from_trainer
-model-index:
-- name: out
-  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. -->
+[<img src="https://replicate.delivery/pbxt/hUbveieQTckemJZxBKfeevvU27tecETYadPoYkNBsyenJvASSA/out-3.png" alt="CodeLLama Stata 7B" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
 
-[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
-<details><summary>See axolotl config</summary>
-
-axolotl version: `0.4.0`
-```yaml
-base_model: codellama/CodeLlama-7b-hf
-tokenizer_type: LlamaTokenizer
-is_llama_derived_model: true
-
-load_in_8bit: false
-load_in_4bit: false
-strict: false
-
-datasets:
-  - path: wndknd/stata
-    type: completion
-dataset_prepared_path: last_run_prepared
-val_set_size: 0.05
-output_dir: ./out
-
-sequence_len: 4096
-sample_packing: true
-pad_to_sequence_len: true
-
-adapter:
-lora_model_dir:
-lora_r:
-lora_alpha:
-lora_dropout:
-lora_target_linear:
-lora_fan_in_fan_out:
-
-wandb_project:
-wandb_entity:
-wandb_watch:
-wandb_name:
-wandb_log_model:
-
-gradient_accumulation_steps: 1
-micro_batch_size: 1
-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:
-tf32: false
-
-gradient_checkpointing: true
-early_stopping_patience:
-resume_from_checkpoint:
-local_rank:
-logging_steps: 1
-xformers_attention:
-flash_attention: true
-flash_attn_cross_entropy: false
-flash_attn_rms_norm: true
-flash_attn_fuse_qkv: false
-flash_attn_fuse_mlp: true
-
-warmup_steps: 100
-evals_per_epoch: 4
-eval_table_size:
-saves_per_epoch: 1
-debug:
-deepspeed: #deepspeed_configs/zero2.json # multi-gpu only
-weight_decay: 0.1
-fsdp:
-fsdp_config:
-special_tokens:
-
-```
-
-</details><br>
-
-# out
-
-This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.0146
-
-## 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: 1
-- eval_batch_size: 1
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 100
-- num_epochs: 1
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 0.4999        | 0.0   | 1    | 1.0117          |
-| 2.6581        | 0.25  | 129  | 1.6428          |
-| 1.4897        | 0.5   | 258  | 1.3088          |
-| 0.0849        | 0.75  | 387  | 1.0146          |
-
-
-### Framework versions
-
-- Transformers 4.37.0
-- Pytorch 2.1.1+cu121
-- Datasets 2.16.1
-- Tokenizers 0.15.0
+A finetuned CodeLlama-7b on 100.000 stata tokens