Transformers
TensorFlow
TensorBoard
Safetensors
t5
text2text-generation
generated_from_keras_callback
text-generation-inference
Instructions to use Ayon128/T5_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayon128/T5_Model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayon128/T5_Model") model = AutoModelForSeq2SeqLM.from_pretrained("Ayon128/T5_Model") - Notebooks
- Google Colab
- Kaggle
Training in progress epoch 0
Browse files- README.md +53 -0
- config.json +1 -1
- generation_config.json +7 -0
- tf_model.h5 +3 -0
- tokenizer.json +4 -2
README.md
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---
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base_model: csebuetnlp/banglat5
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tags:
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- generated_from_keras_callback
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model-index:
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- name: Ayon128/t5_model
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# Ayon128/t5_model
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This model is a fine-tuned version of [csebuetnlp/banglat5](https://huggingface.co/csebuetnlp/banglat5) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 3.7751
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- Validation Loss: 1.0018
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- Epoch: 0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 15000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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- training_precision: mixed_float16
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### Training results
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| Train Loss | Validation Loss | Epoch |
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|:----------:|:---------------:|:-----:|
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| 3.7751 | 1.0018 | 0 |
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### Framework versions
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- Transformers 4.35.2
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- TensorFlow 2.14.0
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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config.json
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"relative_attention_num_buckets": 32,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.35.
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"use_cache": true,
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"vocab_size": 32128
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}
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"relative_attention_num_buckets": 32,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"use_cache": true,
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"vocab_size": 32128
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}
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generation_config.json
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{
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"_from_model_config": true,
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.35.2"
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:504036ebe07f12e3b28d4d7efd7947c23d603a5aee8f1aeebc6ae60b267c0c85
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size 1188285040
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tokenizer.json
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"pre_tokenizer": {
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"type": "Metaspace",
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"replacement": "▁",
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"add_prefix_space": true
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},
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"post_processor": {
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"type": "TemplateProcessing",
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"decoder": {
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"type": "Metaspace",
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"replacement": "▁",
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"add_prefix_space": true
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},
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"model": {
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"type": "Unigram",
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"pre_tokenizer": {
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"type": "Metaspace",
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"replacement": "▁",
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"add_prefix_space": true,
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"prepend_scheme": "always"
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},
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"post_processor": {
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"type": "TemplateProcessing",
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"decoder": {
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"type": "Metaspace",
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"replacement": "▁",
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"add_prefix_space": true,
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"prepend_scheme": "always"
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},
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"model": {
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"type": "Unigram",
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