README.md

metadata

license: apache-2.0
base_model: google/t5-efficient-tiny
tags:
  - generated_from_trainer
datasets:
  - generator
metrics:
  - precision
  - recall
  - f1
model-index:
  - name: salt_language_Classification
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: generator
          type: generator
          config: default
          split: train
          args: default
        metrics:
          - name: Precision
            type: precision
            value: 1
          - name: Recall
            type: recall
            value: 1
          - name: F1
            type: f1
            value: 1

salt_language_Classification

This model is a fine-tuned version of google/t5-efficient-tiny on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 0.0
• Precision: 1.0
• Recall: 1.0
• F1: 1.0

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: 0.001
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 10
• training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.0	0.025	500	0.0	1.0	1.0	1.0
0.0	0.05	1000	0.0	1.0	1.0	1.0
0.0	0.075	1500	0.0	1.0	1.0	1.0
0.0	0.1	2000	0.0	1.0	1.0	1.0
0.0	0.125	2500	0.0	1.0	1.0	1.0
0.0	0.15	3000	0.0	1.0	1.0	1.0
0.0	0.175	3500	0.0	1.0	1.0	1.0
0.0	0.2	4000	0.0	1.0	1.0	1.0
0.0	0.225	4500	0.0	1.0	1.0	1.0
0.0	0.25	5000	0.0	1.0	1.0	1.0
0.0	0.275	5500	0.0	1.0	1.0	1.0
0.0	0.3	6000	0.0	1.0	1.0	1.0
0.0	0.325	6500	0.0	1.0	1.0	1.0
0.0	0.35	7000	0.0	1.0	1.0	1.0
0.0	0.375	7500	0.0	1.0	1.0	1.0
0.0	0.4	8000	0.0	1.0	1.0	1.0
0.0	0.425	8500	0.0	1.0	1.0	1.0
0.0	0.45	9000	0.0	1.0	1.0	1.0
0.0	0.475	9500	0.0	1.0	1.0	1.0
0.0	0.5	10000	0.0	1.0	1.0	1.0
0.0	0.525	10500	0.0	1.0	1.0	1.0
0.0	0.55	11000	0.0	1.0	1.0	1.0
0.0	0.575	11500	0.0	1.0	1.0	1.0
0.0	0.6	12000	0.0	1.0	1.0	1.0
0.0	0.625	12500	0.0	1.0	1.0	1.0
0.0	0.65	13000	0.0	1.0	1.0	1.0
0.0	0.675	13500	0.0	1.0	1.0	1.0
0.0	0.7	14000	0.0	1.0	1.0	1.0
0.0	0.725	14500	0.0	1.0	1.0	1.0
0.0	0.75	15000	0.0	1.0	1.0	1.0
0.0	0.775	15500	0.0	1.0	1.0	1.0
0.0	0.8	16000	0.0	1.0	1.0	1.0
0.0	0.825	16500	0.0	1.0	1.0	1.0
0.0	0.85	17000	0.0	1.0	1.0	1.0
0.0	0.875	17500	0.0	1.0	1.0	1.0
0.0	0.9	18000	0.0	1.0	1.0	1.0
0.0	0.925	18500	0.0	1.0	1.0	1.0
0.0	0.95	19000	0.0	1.0	1.0	1.0
0.0	0.975	19500	0.0	1.0	1.0	1.0
0.0	1.0	20000	0.0	1.0	1.0	1.0

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1