nizar-sayad
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Training in progress epoch 0
Browse files- README.md +53 -0
- config.json +31 -0
- generation_config.json +7 -0
- logs/train/events.out.tfevents.1680763908.f80fec23244c.916.0.v2 +3 -0
- logs/validation/events.out.tfevents.1680764437.f80fec23244c.916.1.v2 +3 -0
- merges.txt +0 -0
- special_tokens_map.json +30 -0
- tf_model.h5 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +41 -0
- vocab.json +0 -0
README.md
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---
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license: other
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tags:
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- generated_from_keras_callback
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model-index:
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- name: nizar-sayad/opt-350m-finetuned-openbookcorpus
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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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# nizar-sayad/opt-350m-finetuned-openbookcorpus
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This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 3.2144
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- Validation Loss: 3.7865
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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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
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- training_precision: float32
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### Training results
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| Train Loss | Validation Loss | Epoch |
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|:----------:|:---------------:|:-----:|
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| 3.2144 | 3.7865 | 0 |
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### Framework versions
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- Transformers 4.27.4
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- TensorFlow 2.12.0
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "facebook/opt-350m",
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"_remove_final_layer_norm": false,
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"OPTForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 2,
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"do_layer_norm_before": false,
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"dropout": 0.1,
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"enable_bias": true,
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"eos_token_id": 2,
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"ffn_dim": 4096,
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"hidden_size": 1024,
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"init_std": 0.02,
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"layer_norm_elementwise_affine": true,
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"layerdrop": 0.0,
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"max_position_embeddings": 2048,
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"model_type": "opt",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"pad_token_id": 1,
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"prefix": "</s>",
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"torch_dtype": "float16",
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"transformers_version": "4.27.4",
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"use_cache": true,
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"vocab_size": 50272,
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"word_embed_proj_dim": 512
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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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"bos_token_id": 2,
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"eos_token_id": 2,
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"pad_token_id": 1,
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"transformers_version": "4.27.4"
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}
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logs/train/events.out.tfevents.1680763908.f80fec23244c.916.0.v2
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version https://git-lfs.github.com/spec/v1
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oid sha256:09fe447d16c9dbdd1ef169dd79119df7f7373767c732a20013b616f4a72a0643
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size 4275784
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logs/validation/events.out.tfevents.1680764437.f80fec23244c.916.1.v2
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version https://git-lfs.github.com/spec/v1
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oid sha256:a1430b521f887258890a3a9d8d3b56e3ee98ba2d464404eb0744dcfa9712d0bc
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size 232
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merges.txt
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special_tokens_map.json
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{
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"bos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"lstrip": false,
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"normalized": true,
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"pad_token": {
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"lstrip": false,
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"normalized": true,
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"unk_token": {
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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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 sha256:0c4a23898c873e3d32e1c23274e029cb24e52cd484b0854ca742e6b0c071f4b2
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size 1325195672
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tokenizer.json
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_prefix_space": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"__type": "AddedToken",
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"errors": "replace",
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"model_max_length": 1000000000000000019884624838656,
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"num_proc": 4,
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"pad_token": {
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"__type": "AddedToken",
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"content": "<pad>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"special_tokens_map_file": null,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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vocab.json
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