Instructions to use Chae/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chae/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Chae/results")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chae/results") model = AutoModelForQuestionAnswering.from_pretrained("Chae/results") - Notebooks
- Google Colab
- Kaggle
bertcraft-data2
Browse files- README.md +7 -8
- model.safetensors +2 -2
- tokenizer.json +2 -2
README.md
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model-index:
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- name: results
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results: []
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pipeline_tag: conversational
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.
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- Exact Match:
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- F1:
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
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| No log | 1.0 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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model-index:
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- name: results
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5909
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- Exact Match: 5.7224
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- F1: 10.3127
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
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| No log | 1.0 | 380 | 2.7182 | 3.5093 | 8.2470 |
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| 2.8171 | 2.0 | 760 | 2.5752 | 5.3430 | 10.5520 |
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| 2.3508 | 3.0 | 1140 | 2.5909 | 5.7224 | 10.3127 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:22effa13b34afbefc469dd82526a6d886586aeffb328d39ac77361374a4c372c
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size 267113240
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tokenizer.json
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"version": "1.0",
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"truncation": {
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"max_length":
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"strategy": "OnlySecond",
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"stride": 128
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"padding": {
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"strategy": {
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"Fixed":
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"direction": "Right",
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"pad_to_multiple_of": null,
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length": 500,
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"strategy": "OnlySecond",
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"stride": 128
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"padding": {
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"strategy": {
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"Fixed": 500
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"direction": "Right",
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"pad_to_multiple_of": null,
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