Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use RottenLemons/flan-t5-base-downsamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RottenLemons/flan-t5-base-downsamples with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RottenLemons/flan-t5-base-downsamples") model = AutoModelForSeq2SeqLM.from_pretrained("RottenLemons/flan-t5-base-downsamples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from RottenLemons/flan-t5-base-downsamples: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/RottenLemons/flan-t5-base-downsamples/resolve/main/README.md
- Command line
-
hf download hf://RottenLemons/flan-t5-base-downsamples/README.md
-
curl -L -o README.md https://huggingface.co/RottenLemons/flan-t5-base-downsamples/resolve/main/README.md
1.2 kB
metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: flan-t5-base-downsamples
results: []
flan-t5-base-downsamples
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0041
- F1: 99.1107
- Gen Len: 2.0630
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.13.1
- Tokenizers 0.13.3