Instructions to use sravanthib/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sravanthib/model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "sravanthib/model") - Notebooks
- Google Colab
- Kaggle
Training completed
Browse files- all_results.json +5 -5
- train_results.json +5 -5
- trainer_state.json +13 -13
all_results.json
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"total_flos":
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"train_runtime":
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{
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"total_flos": 1.6697353660111258e+17,
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"train_loss": 2.030022064844767,
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"train_runtime": 481.4543,
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"train_samples_per_second": 9.97,
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"train_steps_per_second": 0.062
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train_results.json
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{
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"epoch": 0.0547945205479452,
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"total_flos":
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"train_loss": 2.
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"train_runtime":
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"train_steps_per_second": 0.
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{
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"epoch": 0.0547945205479452,
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"total_flos": 1.6697353660111258e+17,
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"train_loss": 2.030022064844767,
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"train_runtime": 481.4543,
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"train_samples_per_second": 9.97,
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"train_steps_per_second": 0.062
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}
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trainer_state.json
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"log_history": [
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{
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"grad_norm":
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"loss":
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"step": 10
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{
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"grad_norm":
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"loss": 1.
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{
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"learning_rate": 0.0001,
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"loss": 0.
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{
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"step": 30,
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"total_flos":
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"train_loss": 2.
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"train_steps_per_second": 0.
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],
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"logging_steps": 10,
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"max_steps": 30,
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"num_input_tokens_seen": 0,
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"num_train_epochs": 1,
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"save_steps":
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"stateful_callbacks": {
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"TrainerControl": {
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"args": {
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"attributes": {}
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"total_flos":
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"train_batch_size": 2,
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"trial_name": null,
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"trial_params": null
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"log_history": [
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{
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"grad_norm": 1.4427909851074219,
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"loss": 4.6764,
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"step": 10
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{
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"epoch": 0.0365296803652968,
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"grad_norm": 4.036961555480957,
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"loss": 1.0438,
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{
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"epoch": 0.0547945205479452,
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"loss": 0.3698,
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{
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"epoch": 0.0547945205479452,
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"step": 30,
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"total_flos": 1.6697353660111258e+17,
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"train_loss": 2.030022064844767,
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"train_runtime": 481.4543,
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"train_samples_per_second": 9.97,
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"train_steps_per_second": 0.062
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}
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],
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"logging_steps": 10,
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"num_input_tokens_seen": 0,
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"num_train_epochs": 1,
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"save_steps": 30,
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"stateful_callbacks": {
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"TrainerControl": {
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"args": {
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"attributes": {}
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}
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"total_flos": 1.6697353660111258e+17,
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"train_batch_size": 2,
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