andysalerno
/

rainbowfish-v7

PEFT

Safetensors

mistral

axolotl

Generated from Trainer

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andysalerno commited on Feb 8, 2024

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 ---
-library_name: transformers
-tags: []
 ---
-# 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. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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-## Uses
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 ---
+license: apache-2.0
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: andysalerno/mistral-sft-v3
+model-index:
+- name: rainbowfish-v7
+  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://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: andysalerno/mistral-sft-v3
+model_type: AutoModelForCausalLM
+load_in_8bit: true
+load_in_4bit: false
+strict: false
+datasets:
+  - path: andysalerno/rainbowfish-v1
+    type:
+      system_prompt: ""
+      field_system: system
+      field_instruction: input
+      field_output: output
+      format: "{instruction}"
+      no_input_format: "{instruction}"
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.005
+output_dir: ./lora-out-rainbow7
+adapter: lora
+lora_model_dir:
+sequence_len: 2048
+sample_packing: false # was true
+eval_sample_packing: false
+pad_to_sequence_len: false
+padding_side: left
+lora_r: 64
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+lora_modules_to_save:
+  - embed_tokens
+  - lm_head
+wandb_project: axolotl
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+gradient_accumulation_steps: 4
+micro_batch_size: 4
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 2e-5
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16:
+tf32: false
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+# early_stopping_patience: 3
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+hub_strategy: "every_save"
+hub_model_id: andysalerno/rainbowfish-v7
+num_epochs: 2
+warmup_steps: 100
+# warmup_ratio: 0.1
+eval_steps: 200
+eval_table_size:
+eval_table_max_new_tokens: 128
+# save_steps: 5
+# max_steps: 400
+saves_per_epoch: 2
+debug:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<|im_start|>"
+  eos_token: "<|im_end|>"
+  unk_token: "<unk>"
+```
+</details><br>
+# rainbowfish-v7
+This model is a fine-tuned version of [andysalerno/mistral-sft-v3](https://huggingface.co/andysalerno/mistral-sft-v3) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6464
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 2
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.6514        | 0.18  | 200  | 0.6828          |
+| 0.6875        | 0.37  | 400  | 0.6691          |
+| 0.6626        | 0.55  | 600  | 0.6625          |
+| 0.688         | 0.74  | 800  | 0.6558          |
+| 0.7143        | 0.92  | 1000 | 0.6520          |
+| 0.5243        | 1.11  | 1200 | 0.6495          |
+| 0.6205        | 1.29  | 1400 | 0.6482          |
+| 0.6159        | 1.47  | 1600 | 0.6469          |
+| 0.6287        | 1.66  | 1800 | 0.6465          |
+| 0.6606        | 1.84  | 2000 | 0.6464          |
+### Framework versions
+- PEFT 0.8.2
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0