update readme

README.md

@@ -5,198 +5,121 @@ library_name: peft
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
 
+This is a [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) model fine-tuned on [Reddit-Dad-Jokes dataset](https://huggingface.co/datasets/shuttie/dadjokes). It can generate cringe and toxic jokes on any short prompt:
 
+```
+[INST] What horse says when she sees an old lady? [/INST] Move over grandma, I'm going to trot!
+[INST] What is a lawyer's favorite drink? [/INST] Whine.
+[INST] My obese pet parrot died over the weekend. [/INST] Now I just have a big fat birdcage.
+[INST] My wife asked why there was a blanket on top of me and my laptop. [/INST] I told her that I was just covering all my bases.
+[INST] My girlfriend changed after she became a vegetarian. [/INST] She finally lost her meat.
+```
 
-## Model Details
+## Demo
 
-### Model Description
+The model is running on HF Spaces: [https://huggingface.co/spaces/shuttie/dadjokes](https://huggingface.co/spaces/shuttie/dadjokes)
 
-<!-- Provide a longer summary of what this model is. -->
+## Used data
 
+We use a [Kaggle Reddit Dad Jokes dataset](https://huggingface.co/datasets/shuttie/reddit-dadjokes) formatted in a base+punchline tuples. The model task was to predict the punchline given the base. Prompt format is the same as for original Mistral model:
 
+`[INST] base [/INST] punchline`
 
-- **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]
+## Training process
 
-### Model Sources [optional]
+The model was trained with [Axolotl](TODO) with the following config:
 
-<!-- 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 0.11.1
+```yaml
+base_model: mistralai/Mistral-Nemo-Base-2407
+model_type: MistralForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+val_set_size: 0.01
+datasets:
+  - path: shuttie/reddit-dadjokes
+    split: train
+    type: 
+      field_system: system
+      field_instruction: instruction
+      field_output: output
+      field_input: input
+      format: "[INST] {input} [/INST]"
+
+dataset_prepared_path: last_run_prepared
+output_dir: ./outputs/dadjoke-mistral-nemo-qlora-r128
+
+adapter: qlora
+lora_model_dir:
+
+sequence_len: 256
+sample_packing: false
+pad_to_sequence_len: true
+
+lora_r: 128
+lora_alpha: 64
+lora_dropout: 0.05
+lora_target_modules:
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project: "dad jokes"
+wandb_entity:
+wandb_watch:
+wandb_name: 
+wandb_log_model:
+
+gradient_accumulation_steps: 1
+micro_batch_size: 16
+num_epochs: 1
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0001
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: false
+gradient_checkpointing_kwargs:
+  use_reentrant: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+xformers_attention:
+flash_attention: true
+
+logging_steps: 10
+warmup_steps: 10
+evals_per_epoch: 10
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: false
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: false
+  fsdp_transformer_layer_cls_to_wrap: MistralDecoderLayer
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  activation_checkpointing: true
+special_tokens:
+  pad_token: <pad>
+flash_attention: true
+```
+
+# License
+
+Apache 2.0