rreit/gemma-7b-prompts

README.md

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+---
+license: other
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: google/gemma-7b
+model-index:
+- name: gemma-7b-prompts
+  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. -->
+
+# gemma-7b-prompts
+
+This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3761
+
+## 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: 0.0004
+- train_batch_size: 1
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- training_steps: 2000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.7687        | 0.09  | 100  | 1.1701          |
+| 0.7207        | 0.19  | 200  | 1.0388          |
+| 0.7185        | 0.28  | 300  | 0.9201          |
+| 0.9138        | 0.38  | 400  | 0.8356          |
+| 0.6879        | 0.47  | 500  | 0.7887          |
+| 0.559         | 0.56  | 600  | 0.7439          |
+| 0.5832        | 0.66  | 700  | 0.7136          |
+| 0.556         | 0.75  | 800  | 0.6738          |
+| 0.5783        | 0.85  | 900  | 0.6341          |
+| 0.6397        | 0.94  | 1000 | 0.6029          |
+| 0.3719        | 1.03  | 1100 | 0.5467          |
+| 0.5698        | 1.13  | 1200 | 0.5181          |
+| 0.6411        | 1.22  | 1300 | 0.4972          |
+| 0.6049        | 1.32  | 1400 | 0.4737          |
+| 0.5309        | 1.41  | 1500 | 0.4417          |
+| 0.4735        | 1.5   | 1600 | 0.4218          |
+| 0.5055        | 1.6   | 1700 | 0.4065          |
+| 0.5309        | 1.69  | 1800 | 0.3900          |
+| 0.5644        | 1.79  | 1900 | 0.3792          |
+| 0.3979        | 1.88  | 2000 | 0.3761          |
+
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.39.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "google/gemma-7b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "v_proj",
+    "o_proj",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 48

training_args.bin

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