Model save

README.md

@@ -0,0 +1,57 @@
+---
+base_model: barc0/Llama-3.1-ARC-Potpourri-Induction-8B
+library_name: transformers
+model_name: potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-warm-start
+tags:
+- generated_from_trainer
+- trl
+- sft
+licence: license
+---
+
+# Model Card for potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-warm-start
+
+This model is a fine-tuned version of [barc0/Llama-3.1-ARC-Potpourri-Induction-8B](https://huggingface.co/barc0/Llama-3.1-ARC-Potpourri-Induction-8B).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="suehyunpark/potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-warm-start", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/suehyun/arc-improve/runs/wuu60040)
+
+This model was trained with SFT.
+
+### Framework versions
+
+- TRL: 0.12.0
+- Transformers: 4.46.2
+- Pytorch: 2.5.1
+- Datasets: 3.1.0
+- Tokenizers: 0.20.3
+
+## Citations
+
+
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

all_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 3.0,
+    "total_flos": 3783747502080.0,
+    "train_loss": 0.5461173463198874,
+    "train_runtime": 901.4481,
+    "train_samples": 169,
+    "train_samples_per_second": 0.562,
+    "train_steps_per_second": 0.02
+}

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.46.2"
+}

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 3.0,
+    "total_flos": 3783747502080.0,
+    "train_loss": 0.5461173463198874,
+    "train_runtime": 901.4481,
+    "train_samples": 169,
+    "train_samples_per_second": 0.562,
+    "train_steps_per_second": 0.02
+}

trainer_state.json

@@ -0,0 +1,192 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 3.0,
+  "eval_steps": 500,
+  "global_step": 18,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.16666666666666666,
+      "grad_norm": 236.14656987198234,
+      "learning_rate": 5e-06,
+      "loss": 2.5604,
+      "step": 1
+    },
+    {
+      "epoch": 0.3333333333333333,
+      "grad_norm": 201.89433604340425,
+      "learning_rate": 1e-05,
+      "loss": 2.1833,
+      "step": 2
+    },
+    {
+      "epoch": 0.5,
+      "grad_norm": 43.15775775201472,
+      "learning_rate": 9.903926402016153e-06,
+      "loss": 0.9756,
+      "step": 3
+    },
+    {
+      "epoch": 0.6666666666666666,
+      "grad_norm": 13.315262915709834,
+      "learning_rate": 9.619397662556434e-06,
+      "loss": 0.7236,
+      "step": 4
+    },
+    {
+      "epoch": 0.8333333333333334,
+      "grad_norm": 8.220944289845372,
+      "learning_rate": 9.157348061512728e-06,
+      "loss": 0.4679,
+      "step": 5
+    },
+    {
+      "epoch": 1.0,
+      "grad_norm": 16.58577267851266,
+      "learning_rate": 8.535533905932739e-06,
+      "loss": 0.402,
+      "step": 6
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 0.32322201132774353,
+      "eval_runtime": 1.0011,
+      "eval_samples_per_second": 8.99,
+      "eval_steps_per_second": 2.997,
+      "step": 6
+    },
+    {
+      "epoch": 1.1666666666666667,
+      "grad_norm": 2.76249506004443,
+      "learning_rate": 7.777851165098012e-06,
+      "loss": 0.2663,
+      "step": 7
+    },
+    {
+      "epoch": 1.3333333333333333,
+      "grad_norm": 2.763402651988573,
+      "learning_rate": 6.913417161825449e-06,
+      "loss": 0.2429,
+      "step": 8
+    },
+    {
+      "epoch": 1.5,
+      "grad_norm": 3.883639510915858,
+      "learning_rate": 5.975451610080643e-06,
+      "loss": 0.2455,
+      "step": 9
+    },
+    {
+      "epoch": 1.6666666666666665,
+      "grad_norm": 3.161760936759259,
+      "learning_rate": 5e-06,
+      "loss": 0.2269,
+      "step": 10
+    },
+    {
+      "epoch": 1.8333333333333335,
+      "grad_norm": 2.335011386155214,
+      "learning_rate": 4.02454838991936e-06,
+      "loss": 0.2229,
+      "step": 11
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 1.716063572976715,
+      "learning_rate": 3.0865828381745515e-06,
+      "loss": 0.1921,
+      "step": 12
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 0.24893158674240112,
+      "eval_runtime": 0.9909,
+      "eval_samples_per_second": 9.083,
+      "eval_steps_per_second": 3.028,
+      "step": 12
+    },
+    {
+      "epoch": 2.1666666666666665,
+      "grad_norm": 0.8996504564335516,
+      "learning_rate": 2.2221488349019903e-06,
+      "loss": 0.1879,
+      "step": 13
+    },
+    {
+      "epoch": 2.3333333333333335,
+      "grad_norm": 1.3172641910170275,
+      "learning_rate": 1.4644660940672628e-06,
+      "loss": 0.1706,
+      "step": 14
+    },
+    {
+      "epoch": 2.5,
+      "grad_norm": 1.0444149673130907,
+      "learning_rate": 8.426519384872733e-07,
+      "loss": 0.1959,
+      "step": 15
+    },
+    {
+      "epoch": 2.6666666666666665,
+      "grad_norm": 0.6948355165030632,
+      "learning_rate": 3.8060233744356634e-07,
+      "loss": 0.2043,
+      "step": 16
+    },
+    {
+      "epoch": 2.8333333333333335,
+      "grad_norm": 0.6328551118621334,
+      "learning_rate": 9.607359798384785e-08,
+      "loss": 0.1693,
+      "step": 17
+    },
+    {
+      "epoch": 3.0,
+      "grad_norm": 0.7570021616382325,
+      "learning_rate": 0.0,
+      "loss": 0.1928,
+      "step": 18
+    },
+    {
+      "epoch": 3.0,
+      "eval_loss": 0.23970693349838257,
+      "eval_runtime": 0.9997,
+      "eval_samples_per_second": 9.002,
+      "eval_steps_per_second": 3.001,
+      "step": 18
+    },
+    {
+      "epoch": 3.0,
+      "step": 18,
+      "total_flos": 3783747502080.0,
+      "train_loss": 0.5461173463198874,
+      "train_runtime": 901.4481,
+      "train_samples_per_second": 0.562,
+      "train_steps_per_second": 0.02
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 18,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 3783747502080.0,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}