Update README.md
Browse files
README.md
CHANGED
|
@@ -9,7 +9,7 @@ library_name: sentence-transformers
|
|
| 9 |
metrics:
|
| 10 |
- spearmanr
|
| 11 |
license: apache-2.0
|
| 12 |
-
new_version: Derify/ChemMRL
|
| 13 |
---
|
| 14 |
|
| 15 |
# Chem-MRL (SentenceTransformer)
|
|
@@ -20,13 +20,9 @@ This is a trained [Chem-MRL](https://github.com/emapco/chem-mrl) [sentence-trans
|
|
| 20 |
|
| 21 |
### Model Description
|
| 22 |
- **Model Type:** Sentence Transformer
|
| 23 |
-
<!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
|
| 24 |
- **Maximum Sequence Length:** 128 tokens
|
| 25 |
- **Output Dimensionality:** 1024 dimensions
|
| 26 |
- **Similarity Function:** Cosine Similarity
|
| 27 |
-
<!-- - **Training Dataset:** Unknown -->
|
| 28 |
-
<!-- - **Language:** Unknown -->
|
| 29 |
-
<!-- - **License:** Unknown -->
|
| 30 |
|
| 31 |
### Model Sources
|
| 32 |
|
|
@@ -75,42 +71,6 @@ print(similarities.shape)
|
|
| 75 |
# [3, 3]
|
| 76 |
```
|
| 77 |
|
| 78 |
-
<!--
|
| 79 |
-
### Direct Usage (Transformers)
|
| 80 |
-
|
| 81 |
-
<details><summary>Click to see the direct usage in Transformers</summary>
|
| 82 |
-
|
| 83 |
-
</details>
|
| 84 |
-
-->
|
| 85 |
-
|
| 86 |
-
<!--
|
| 87 |
-
### Downstream Usage (Sentence Transformers)
|
| 88 |
-
|
| 89 |
-
You can finetune this model on your own dataset.
|
| 90 |
-
|
| 91 |
-
<details><summary>Click to expand</summary>
|
| 92 |
-
|
| 93 |
-
</details>
|
| 94 |
-
-->
|
| 95 |
-
|
| 96 |
-
<!--
|
| 97 |
-
### Out-of-Scope Use
|
| 98 |
-
|
| 99 |
-
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
| 100 |
-
-->
|
| 101 |
-
|
| 102 |
-
<!--
|
| 103 |
-
## Bias, Risks and Limitations
|
| 104 |
-
|
| 105 |
-
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
| 106 |
-
-->
|
| 107 |
-
|
| 108 |
-
<!--
|
| 109 |
-
### Recommendations
|
| 110 |
-
|
| 111 |
-
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
| 112 |
-
-->
|
| 113 |
-
|
| 114 |
## Training Details
|
| 115 |
|
| 116 |
### Framework Versions
|
|
@@ -131,7 +91,6 @@ You can finetune this model on your own dataset.
|
|
| 131 |
- Li, Xiaoya, et al. "Dice Loss for Data-imbalanced NLP Tasks." _arXiv [Cs.CL]_, 2020. [Link](https://arxiv.org/abs/1911.02855)
|
| 132 |
- Reimers, Nils, and Gurevych, Iryna. "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks." _Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing_, 2019. [Link](https://arxiv.org/abs/1908.10084).
|
| 133 |
|
| 134 |
-
|
| 135 |
## Model Card Authors
|
| 136 |
|
| 137 |
[@eacortes](https://huggingface.co/eacortes)
|
|
|
|
| 9 |
metrics:
|
| 10 |
- spearmanr
|
| 11 |
license: apache-2.0
|
| 12 |
+
new_version: Derify/ChemMRL
|
| 13 |
---
|
| 14 |
|
| 15 |
# Chem-MRL (SentenceTransformer)
|
|
|
|
| 20 |
|
| 21 |
### Model Description
|
| 22 |
- **Model Type:** Sentence Transformer
|
|
|
|
| 23 |
- **Maximum Sequence Length:** 128 tokens
|
| 24 |
- **Output Dimensionality:** 1024 dimensions
|
| 25 |
- **Similarity Function:** Cosine Similarity
|
|
|
|
|
|
|
|
|
|
| 26 |
|
| 27 |
### Model Sources
|
| 28 |
|
|
|
|
| 71 |
# [3, 3]
|
| 72 |
```
|
| 73 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 74 |
## Training Details
|
| 75 |
|
| 76 |
### Framework Versions
|
|
|
|
| 91 |
- Li, Xiaoya, et al. "Dice Loss for Data-imbalanced NLP Tasks." _arXiv [Cs.CL]_, 2020. [Link](https://arxiv.org/abs/1911.02855)
|
| 92 |
- Reimers, Nils, and Gurevych, Iryna. "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks." _Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing_, 2019. [Link](https://arxiv.org/abs/1908.10084).
|
| 93 |
|
|
|
|
| 94 |
## Model Card Authors
|
| 95 |
|
| 96 |
[@eacortes](https://huggingface.co/eacortes)
|