Training
Browse files- README.md +18 -29
- config.json +1 -1
- generation_config.json +1 -1
- model.safetensors +3 -0
- runs/Jan23_06-13-55_1fca61cf9468/events.out.tfevents.1705990445.1fca61cf9468.26.0 +3 -0
- special_tokens_map.json +21 -3
- tokenizer.json +6 -3
- tokenizer_config.json +27 -1
- training_args.bin +2 -2
README.md
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license: apache-2.0
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base_model: IlyaGusev/rut5_base_sum_gazeta
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tags:
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metrics:
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- rouge
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model-index:
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- name: rut5_base_sum_gazeta-finetuned_week_gpt
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results: []
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---
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This model is suitable for summarizing Hubr articles.
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It achieves the following results on the evaluation set:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5.6e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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| 1.7691 | 1.0 | 1110 | 1.4005 | 37.7689 | 17.7394 | 36.8468 | 36.8842 |
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| 1.4892 | 2.0 | 2220 | 1.3477 | 35.9349 | 16.8403 | 35.1786 | 35.2055 |
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| 1.3579 | 3.0 | 3330 | 1.3079 | 37.7579 | 17.6421 | 36.8439 | 36.8182 |
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| 1.2708 | 4.0 | 4440 | 1.2675 | 37.867 | 17.3909 | 36.9706 | 36.987 |
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| 1.2006 | 5.0 | 5550 | 1.2703 | 38.8218 | 17.9772 | 38.001 | 37.9811 |
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| 1.1519 | 6.0 | 6660 | 1.2703 | 38.0351 | 17.5386 | 37.209 | 37.1815 |
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| 1.1132 | 7.0 | 7770 | 1.2593 | 38.4673 | 17.8343 | 37.529 | 37.5268 |
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| 1.0932 | 8.0 | 8880 | 1.2643 | 38.9266 | 18.0587 | 38.1447 | 38.1337 |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.
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license: apache-2.0
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base_model: IlyaGusev/rut5_base_sum_gazeta
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tags:
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- summarization
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- generated_from_trainer
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model-index:
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- name: rut5_base_sum_gazeta-finetuned_week_gpt
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# rut5_base_sum_gazeta-finetuned_week_gpt
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This model is a fine-tuned version of [IlyaGusev/rut5_base_sum_gazeta](https://huggingface.co/IlyaGusev/rut5_base_sum_gazeta) on the None dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 2.3331
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- eval_rouge1: 0.0
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- eval_rouge2: 0.0
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- eval_rougeL: 0.0
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- eval_rougeLsum: 0.0
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- eval_runtime: 7.8395
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- eval_samples_per_second: 0.383
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- eval_steps_per_second: 0.128
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- step: 0
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5.6e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 8
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.15.0
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config.json
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 30000
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}
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.36.2",
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"use_cache": true,
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"vocab_size": 30000
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}
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generation_config.json
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"max_length": 200,
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"num_beams": 5,
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"pad_token_id": 0,
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"transformers_version": "4.
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}
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"max_length": 200,
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"num_beams": 5,
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"pad_token_id": 0,
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"transformers_version": "4.36.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e4ea4a6196701370c6d96dd9e35b5e2e625db48c4ab487302dd89d2e8bc8a633
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size 977270632
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runs/Jan23_06-13-55_1fca61cf9468/events.out.tfevents.1705990445.1fca61cf9468.26.0
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version https://git-lfs.github.com/spec/v1
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size 488
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special_tokens_map.json
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{
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"eos_token":
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}
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{
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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"pad_token": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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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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tokenizer.json
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"pre_tokenizer": {
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"type": "Metaspace",
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"replacement": "β",
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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": "β",
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"add_prefix_space": true
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"model": {
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"type": "Unigram",
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"β<extra_id_0>",
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"pre_tokenizer": {
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"type": "Metaspace",
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"replacement": "β",
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"add_prefix_space": true,
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"prepend_scheme": "always"
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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": "β",
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"add_prefix_space": true,
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"prepend_scheme": "always"
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"model": {
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"type": "Unigram",
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"byte_fallback": false
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tokenizer_config.json
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"clean_up_tokenization_spaces": true,
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"eos_token": "</s>",
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training_args.bin
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