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denizzhansahin
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deneme_spor

Text Generation
Transformers
TensorFlow
gpt2
generated_from_keras_callback
Inference Endpoints
text-generation-inference
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  2. config.json +38 -0
  3. generation_config.json +6 -0
  4. tf_model.h5 +3 -0
README.md CHANGED
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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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-
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- ### Downstream Use [optional]
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- ## Bias, Risks, and Limitations
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- ### Recommendations
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- ## Training Details
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- ### Training Data
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- ## Evaluation
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- #### Factors
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- #### Metrics
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- ## Environmental Impact
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ## Glossary [optional]
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- ## More Information [optional]
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  ---
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+ license: mit
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+ base_model: gpt2
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: deneme_spor
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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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+
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+ # deneme_spor
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+
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+ This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 4.9093
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+ - Validation Loss: 5.9538
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+ - Epoch: 149
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': -963, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, '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: float32
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+
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+ ### Training results
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+
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+ | Train Loss | Validation Loss | Epoch |
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+ |:----------:|:---------------:|:-----:|
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+ | 9.1978 | 8.9070 | 0 |
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+ | 8.7400 | 8.5517 | 1 |
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+ | 8.4947 | 8.3909 | 2 |
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+ | 8.3502 | 8.2608 | 3 |
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+ | 8.2126 | 8.1241 | 4 |
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+ | 8.0688 | 7.9827 | 5 |
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+ | 7.9232 | 7.8449 | 6 |
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+ | 7.7844 | 7.7107 | 7 |
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+ | 7.6446 | 7.5719 | 8 |
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+ | 7.4919 | 7.4263 | 9 |
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+ | 7.3429 | 7.2975 | 10 |
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+ | 7.2042 | 7.1774 | 11 |
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+ | 7.0643 | 7.0685 | 12 |
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+ | 6.9229 | 6.9668 | 13 |
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+ | 6.7836 | 6.8770 | 14 |
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+ | 6.6425 | 6.7752 | 15 |
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+ | 6.4982 | 6.6895 | 16 |
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+ | 6.3539 | 6.5963 | 17 |
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+ | 6.2035 | 6.5170 | 18 |
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+ | 6.0612 | 6.4285 | 19 |
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+ | 5.9164 | 6.3429 | 20 |
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+ | 5.7708 | 6.2664 | 21 |
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+ | 5.6249 | 6.1997 | 22 |
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+ | 5.4822 | 6.1348 | 23 |
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+ | 5.3368 | 6.0659 | 24 |
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+ | 5.1959 | 6.0042 | 25 |
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+ | 5.0527 | 5.9525 | 26 |
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+ | 4.9070 | 5.9538 | 27 |
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+ | 4.9062 | 5.9538 | 28 |
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+ | 4.9095 | 5.9538 | 29 |
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+ | 4.9056 | 5.9538 | 30 |
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+ | 4.9071 | 5.9538 | 148 |
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+ | 4.9093 | 5.9538 | 149 |
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - TensorFlow 2.15.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
 
 
 
config.json ADDED
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+ {
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+ "_name_or_path": "gpt2",
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+ "activation_function": "gelu_new",
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+ "architectures": [
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+ "GPT2LMHeadModel"
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+ ],
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+ "attn_pdrop": 0.1,
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+ "bos_token_id": 0,
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+ "embd_pdrop": 0.1,
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+ "eos_token_id": 0,
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+ "initializer_range": 0.02,
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+ "layer_norm_epsilon": 1e-05,
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+ "model_type": "gpt2",
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+ "n_ctx": 100,
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+ "n_embd": 768,
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+ "n_head": 12,
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+ "n_inner": null,
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+ "n_layer": 12,
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+ "n_positions": 1024,
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+ "reorder_and_upcast_attn": false,
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+ "resid_pdrop": 0.1,
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+ "scale_attn_by_inverse_layer_idx": false,
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+ "scale_attn_weights": true,
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+ "summary_activation": null,
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+ "summary_first_dropout": 0.1,
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+ "summary_proj_to_labels": true,
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+ "summary_type": "cls_index",
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+ "summary_use_proj": true,
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+ "task_specific_params": {
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+ "text-generation": {
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+ "do_sample": true,
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+ "max_length": 50
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+ }
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+ },
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+ "transformers_version": "4.38.2",
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+ "use_cache": true,
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+ "vocab_size": 10000
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 0,
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+ "eos_token_id": 0,
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+ "transformers_version": "4.38.2"
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+ }
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