metadata
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: >-
or anyone who was praying for the sight of Al Cliver wrestling a naked,
7ft tall black guy into a full nelson, your film has arrived! Film starlet
Laura Crawford (Ursula Buchfellner) is kidnapped by a group who demand the
ransom of $6 million to be delivered to their island hideaway. What they
don't count on is rugged Vietnam vet Peter Weston (Cliver) being hired by
a film producer to save the girl. And what they really didn't count on was
a local tribe that likes to offer up young women to their monster cannibal
god with bloodshot bug eyes.<br /><br />Pretty much the same filming set
up as CANNIBALS, this one fares a bit better when it comes to
entertainment value, thanks mostly a hilarious dub track and the
impossibly goofy monster with the bulging eyes (Franco confirms they were
split ping pong balls on the disc's interview). Franco gets a strong
EuroCult supporting cast including Gisela Hahn (CONTAMINATION) and Werner
Pochath (whose death is one of the most head-scratching things I ever seen
as a guy who is totally not him is shown - in close up - trying to be
him). The film features tons of nudity and the gore (Tempra paint variety)
is there. The highlight for me was the world's slowly fistfight between
Cliver and Antonio de Cabo in the splashing waves. Sadly, ol' Jess pads
this one out to an astonishing (and, at times, agonizing) 1 hour and 40
minutes when it should have run 80 minutes tops. <br /><br />For the most
part, the Severin DVD looks pretty nice but there are some odd ghosting
images going on during some of the darker scenes. Also, one long section
of dialog is in Spanish with no subs (they are an option, but only when
you listen to the French track). Franco gives a nice 16- minute interview
about the film and has much more pleasant things to say about Buchfellner
than his CANNIBALS star Sabrina Siani.
- text: >-
I saw this film opening weekend in Australia, anticipating with an
excellent cast of Ledger, Edgerton, Bloom, Watts and Rush that the
definitive story of Ned Kelly would unfold before me. Unfortunately,
despite an outstanding performance by Heath Ledger in the lead role, the
plot was paper thin....which doesn't inspire me to read "Our Sunshine".
There were some other plus points, the support acting from Edgerton in
particular, assured direction from Jordan (confirming his talent on show
in Buffalo Soldiers as well), and production design that gave a real feel
of harshness to the Australian bush, much as the Irish immigrants of the
early 19th century must have seen it. But I can't help feeling that
another opportunity has been missed to tell the real story of an
Australian folk hero (or was he?)....in what I suspect is a concession to
Hollywood and selling the picture in the US. Oh well, at least Jordan and
the producers didn't agree to lose the beards just to please
Universal...<br /><br />Guess I will just have to content myself with
Peter Carey's excellent "Secret History of the Kelly Gang". 4/10
- text: >-
THE ZOMBIE CHRONICLES <br /><br />Aspect ratio: 1.33:1 (Nu-View 3-D)<br
/><br />Sound format: Mono<br /><br />Whilst searching for a (literal)
ghost town in the middle of nowhere, a young reporter (Emmy Smith) picks
up a grizzled hitchhiker (Joseph Haggerty) who tells her two stories
involving flesh-eating zombies reputed to haunt the area.<br /><br />An
ABSOLUTE waste of time, hobbled from the outset by Haggerty's painfully
amateurish performance in a key role. Worse still, the two stories which
make up the bulk of the running time are utterly routine, made worse by
indifferent performances and lackluster direction by Brad Sykes,
previously responsible for the likes of CAMP BLOOD (1999). This isn't a
'fun' movie in the sense that Ed Wood's movies are 'fun' (he, at least,
believed in what he was doing and was sincere in his efforts, despite a
lack of talent); Sykes' home-made movies are, in fact, aggravating, boring
and almost completely devoid of any redeeming virtue, and most viewers
will feel justifiably angry and cheated by such unimaginative,
badly-conceived junk. The 3-D format is utterly wasted here.
- text: >-
There are some nice shots in this film, it catches some of the landscapes
with such a beautiful light, in fact the cinematography is probably it's
best asset.<br /><br />But it's basically more of a made for TV movie, and
although it has a lot of twists and turns in the plot, which keeps it
quite interesting viewing, there are no subtitles and key plot
developments are unveiled in Spanish, so non Spanish speakers will be left
a little lost.<br /><br />I had it as a Xmas gift, as it's a family trait
to work through the films of a actor we find talented, and Matthew
Mconaughey was just awesome in "A Time to kill" , and the "The Newton Boys
" so I expressed I wanted to see more of his work.<br /><br />However
although it says on the DVD box it is a Matthew Mconaughey film and uses
this as a marketing ploy, he has a few lines and is on screen for not very
minutes at the end of the film, he is basically an extra and he doesn't
exactly light up the screen while he is on, so die hard fans, really not
worth it from that point of view.<br /><br />The films star though,
Patrick McGaw is great though and very easy on the eye, and his character
is just so nice and kind and caring, a true saint of a guy, he'd be well
written into a ROM com.<br /><br />So for true Mcconaughey acting
brilliance of the ones I've seen, I'd recommend, "A Time to kill" , "The
Newton Boys " "Frailty", "How to Lose a Guy in 10 Days", "Edtv" and
"Amistad" and avoid too "Larger Than Life" and "Angels in the Outfield"
unless you feel like a kids film or have kids around as neither of these
are indicative of his talent, but are quite amusing films for children,
again MM is really nothing more that a supporting artist with just a few
if any lines.<br /><br />As for Scorpion Springit's not a bad film but it
also isn't screen stealing either.
- text: >-
I guess I was attracted to this film both because of the sound of the
story and the leading actor, so I gave it a chance, from director Gregor
Jordan (Buffalo Soldiers). Basically Ned Kelly (Heath Ledger) is set up by
the police, especially Superintendent Francis Hare (Geoffrey Rush), he is
forced to go on the run forming a gang and go against them to clear his
own and his family's names. That's really all I can say about the story,
as I wasn't paying the fullest attention to be honest. Also starring
Orlando Bloom as Joseph Byrne, Naomi Watts as Julia Cook, Laurence Kinlan
as Dan Kelly, Philip Barantini as Steve Hart, Joel Edgerton as Aaron
Sherritt, Kiri Paramore as Constable Fitzpatrick, Kerry Condon as Kate
Kelly, Emily Browning as Grace Kelly and Rachel Griffiths as Susan Scott.
Ledger makes a pretty good performance, for what it's worth, and the film
does have it's eye-catching moments, particularly with a gun battle
towards the end, but I can't say I enjoyed it as I didn't look at it all.
Okay!
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: true
SetFit
This is a SetFit model that can be used for Text Classification. A LogisticRegression instance is used for classification.
The model has been trained using an efficient few-shot learning technique that involves:
- Fine-tuning a Sentence Transformer with contrastive learning.
- Training a classification head with features from the fine-tuned Sentence Transformer.
Model Details
Model Description
- Model Type: SetFit
- Classification head: a LogisticRegression instance
- Maximum Sequence Length: 512 tokens
- Number of Classes: 2 classes
Model Sources
- Repository: SetFit on GitHub
- Paper: Efficient Few-Shot Learning Without Prompts
- Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts
Model Labels
| Label | Examples |
|---|---|
| negative |
|
| positive |
|
Uses
Direct Use for Inference
First install the SetFit library:
pip install setfit
Then you can load this model and run inference.
from setfit import SetFitModel
# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("mahitha-t/text_classification_model")
# Run inference
preds = model("I guess I was attracted to this film both because of the sound of the story and the leading actor, so I gave it a chance, from director Gregor Jordan (Buffalo Soldiers). Basically Ned Kelly (Heath Ledger) is set up by the police, especially Superintendent Francis Hare (Geoffrey Rush), he is forced to go on the run forming a gang and go against them to clear his own and his family's names. That's really all I can say about the story, as I wasn't paying the fullest attention to be honest. Also starring Orlando Bloom as Joseph Byrne, Naomi Watts as Julia Cook, Laurence Kinlan as Dan Kelly, Philip Barantini as Steve Hart, Joel Edgerton as Aaron Sherritt, Kiri Paramore as Constable Fitzpatrick, Kerry Condon as Kate Kelly, Emily Browning as Grace Kelly and Rachel Griffiths as Susan Scott. Ledger makes a pretty good performance, for what it's worth, and the film does have it's eye-catching moments, particularly with a gun battle towards the end, but I can't say I enjoyed it as I didn't look at it all. Okay!")
Training Details
Training Set Metrics
| Training set | Min | Median | Max |
|---|---|---|---|
| Word count | 49 | 233.3125 | 837 |
| Label | Training Sample Count |
|---|---|
| positive | 8 |
| negative | 8 |
Training Hyperparameters
- batch_size: (16, 2)
- num_epochs: (1, 16)
- max_steps: -1
- sampling_strategy: oversampling
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.01
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- l2_weight: 0.01
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
Training Results
| Epoch | Step | Training Loss | Validation Loss |
|---|---|---|---|
| 0.1111 | 1 | 0.1572 | - |
Framework Versions
- Python: 3.11.13
- SetFit: 1.1.2
- Sentence Transformers: 4.1.0
- Transformers: 4.52.4
- PyTorch: 2.6.0+cu124
- Datasets: 3.6.0
- Tokenizers: 0.21.1
Citation
BibTeX
@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}