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Mistral-7B-Instruct-v0.2-4b-r64-task1215
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mistralai/Mistral-7B-Instruct-v0.2
Mistral-7B-Instruct-v0.2-4b-r64-task1215 API & Inference Endpoint | FriendliAIREADME
License: apache-2.0Source
- Base model:
mistralai/Mistral-7B-Instruct-v0.2
- Dataset:
Lots-of-LoRAs/task1215_atomic_classification_capableof
- Train split:
train
- Eval split:
valid
- Task ID:
1215
- Description:
atomic classification capableof
LoRA
- Rank:
64
- Target modules:
q_proj, k_proj, v_proj
- LoRA alpha:
32
- LoRA dropout:
0.05
- Bias:
none
Training protocol
- Base model dtype:
4bit-nf4
- Quantization:
QLoRA 4bit NF4, double quantization enabled, bf16 compute
- Adapter trainable dtype:
float32
- Prompt format:
plain
- Loss: completion-only causal LM cross entropy
- Epochs:
5.0
- Best checkpoint metric:
eval_loss
- Learning rate:
0.0002
- Scheduler:
cosine
- Warmup ratio:
Files
adapter_model.safetensors: LoRA adapter weights
adapter_config.json: PEFT adapter configuration
task_manifest.json: source manifest row and resolved splits
training_protocol.json: fixed protocol used for this run
0.03
Effective batch size: 16Optimizer: paged_adamw_32bit