Training in progress, step 11000

README.md

@@ -1,139 +1,202 @@
 ---
-library_name: peft
-license: apache-2.0
 base_model: echarlaix/tiny-random-PhiForCausalLM
-tags:
-- axolotl
-- generated_from_trainer
-datasets:
-- datasets/58a7025f-2e99-4e25-be15-9885fcb8f1e4.json
-model-index:
-- name: 58a7025f-2e99-4e25-be15-9885fcb8f1e4
-  results: []
+library_name: peft
 ---
 
-<!-- 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. -->
+# Model Card for Model ID
 
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
-<details><summary>See axolotl config</summary>
+<!-- Provide a quick summary of what the model is/does. -->
 
-axolotl version: `0.7.0`
-```yaml
-adam_beta1: 0.9
-adam_beta2: 0.99
-adam_epsilon: 1.0e-08
-adapter: lora
-auto_resume_from_checkpoints: true
-base_model: echarlaix/tiny-random-PhiForCausalLM
-base_model_config: echarlaix/tiny-random-PhiForCausalLM
-bf16: true
-bfloat16: true
-chat_template: llama3
-dataset_exact_deduplication: false
-dataset_prepared_path: data/last_run_prepared
-datasets:
-- path: datasets/58a7025f-2e99-4e25-be15-9885fcb8f1e4.json
-  type:
-    field_input: ''
-    field_instruction: startphrase
-    field_output: gold-ending
-    field_system: system
-    format: '{instruction} {input}'
-    no_input_format: '{instruction}'
-    system_format: '{system}'
-    system_prompt: ''
-eval_batch_size: null
-eval_steps: 1000
-gradient_accumulation_steps: 1
-hf_use_auth_token: true
-hub_model_id: toilaluan/58a7025f-2e99-4e25-be15-9885fcb8f1e4
-learning_rate: 8.0e-05
-lora_alpha: 128
-lora_dropout: 0.1
-lora_fan_in_fan_out: false
-lora_mlp_kernel: true
-lora_model_dir: null
-lora_o_kernel: true
-lora_on_cpu: false
-lora_qkv_kernel: true
-lora_r: 64
-lora_target_modules:
-- q_proj
-- v_proj
-- down_proj
-- up_proj
-- k_proj
-- o_proj
-- gate_proj
-max_grad_norm: 1.0
-max_steps: 5000
-micro_batch_size: 2
-model_type: AutoModelForCausalLM
-num_epochs: 4
-optimizer: adamw_torch
-output_dir: datasets/58a7025f-2e99-4e25-be15-9885fcb8f1e4/checkpoints
-save_steps: 1000
-sequence_len: 2048
-shuffle_merged_datasets: true
-tokenizer_type: AutoTokenizer
-trust_remote_code: true
-val_set_size: 50
-warmup_steps: 100
-weight_decay: 1.0e-06
-
-```
-
-</details><br>
-
-# 58a7025f-2e99-4e25-be15-9885fcb8f1e4
-
-This model is a fine-tuned version of [echarlaix/tiny-random-PhiForCausalLM](https://huggingface.co/echarlaix/tiny-random-PhiForCausalLM) on the datasets/58a7025f-2e99-4e25-be15-9885fcb8f1e4.json dataset.
-It achieves the following results on the evaluation set:
-- Loss: 6.8315
-
-## 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: 8e-05
-- train_batch_size: 2
-- eval_batch_size: 2
-- seed: 42
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.99) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 100
-- training_steps: 5000
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| No log        | 0.0000 | 1    | 6.9371          |
-| 6.8506        | 0.0216 | 1000 | 6.8466          |
-| 6.829         | 0.0431 | 2000 | 6.8359          |
-| 6.8375        | 0.0647 | 3000 | 6.8326          |
-| 6.8319        | 0.0863 | 4000 | 6.8318          |
-| 6.8383        | 0.1079 | 5000 | 6.8315          |
 
 
+## 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 0.13.2
-- Transformers 4.48.3
-- Pytorch 2.6.0+cu124
-- Datasets 3.2.0
-- Tokenizers 0.21.1
+- PEFT 0.13.2

adapter_config.json

@@ -23,13 +23,13 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "q_proj",
-    "up_proj",
+    "down_proj",
     "k_proj",
-    "gate_proj",
     "v_proj",
+    "up_proj",
     "o_proj",
-    "down_proj"
+    "q_proj",
+    "gate_proj"
   ],
   "task_type": "CAUSAL_LM",
   "use_dora": false,

adapter_model.safetensors

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training_args.bin

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